research paper on internet technology

Internet of Things: Current Research, Challenges, Trends and Applications

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• First Online: 11 May 2021
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• Dipankar Debnath 8 &
• Sarat Kr. Chettri 9  

Part of the book series: Algorithms for Intelligent Systems ((AIS))

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The Internet of Things (IoT) has provided a viable opportunity to develop powerful applications for both consumer and industrial use. Since its inception, a wide range of IoT applications have been developed and deployed and their integration with other state-of-the-art technologies has increased many-fold. The main objective of this paper is to review the background and current trends in IoT research, enabling technologies, to identify key IoT applications in industry and open research issues and challenges.

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Dipankar Debnath

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Sarat Kr. Chettri

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Sumit Srivastava

Department of Electrical Engineering, University of Engineering and Management, Jaipur, Rajasthan, India

Bhanu Pratap Soni

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Debnath, D., Chettri, S.K. (2021). Internet of Things: Current Research, Challenges, Trends and Applications. In: Gao, XZ., Kumar, R., Srivastava, S., Soni, B.P. (eds) Applications of Artificial Intelligence in Engineering. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-33-4604-8_52

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Internet of Things: Latest Advances

Dear Colleagues,

The Internet of Things (IoT) is one of the most prominent tech trends to have emerged in recent years. It refers to the fact that while the word “internet” initially referred to the wide-scale networking of computers, today, devices of every size and shape – from cars to kitchen appliances to industrial machinery - are connected and sharing information digitally, on a global scale.

The purpose of this Topic is to bring together state-of-the-art achievements on IoT and its applications. It discusses all aspects of emerging IoT sciences and technologies and serves as a platform for colleagues to exchange novel ideas in this area.

Especially, IoT devices are used in many applications in non-harsh environments. Initially, there were no IoT devices for harsh environments or highly protected expensive IoT devices. However, with the advancement of AI, AI is now able to predict target parameters even without IoT devices in harsh environments. In addition to critical boundaries with IoT devices in non-harsh and harsh environments, this Topic is also interested in how engineers and scientists can cope with and overcome harsh situations by protecting fragile IoT devices, and other technologies including AI technologies that can predict without IoT devices.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). We encourage authors to submit original research articles, case studies, reviews, theoretical and critical perspectives, and viewpoint articles on (but not limited to) the following topics:

• Artificial Intelligence;
• Internet of Things;
• vulnerable sensors;
• AI prediction;
• harsh environments;
• non-harsh environments…
• artificial intelligence
• internet of things
• vulnerable sensors
• AI prediction
• harsh environments
• non-harsh environment
• smart sensing
• smart sensors
• industrial internet of things
• artificial intelligence of things
• internet of medical things

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• Survey Paper
• Open access
• Published: 09 December 2019

Internet of Things is a revolutionary approach for future technology enhancement: a review

• Sachin Kumar   ORCID: orcid.org/0000-0003-3949-0302 1 ,
• Prayag Tiwari 2 &
• Mikhail Zymbler 1  

Journal of Big Data volume  6 , Article number:  111 ( 2019 ) Cite this article

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Internet of Things (IoT) is a new paradigm that has changed the traditional way of living into a high tech life style. Smart city, smart homes, pollution control, energy saving, smart transportation, smart industries are such transformations due to IoT. A lot of crucial research studies and investigations have been done in order to enhance the technology through IoT. However, there are still a lot of challenges and issues that need to be addressed to achieve the full potential of IoT. These challenges and issues must be considered from various aspects of IoT such as applications, challenges, enabling technologies, social and environmental impacts etc. The main goal of this review article is to provide a detailed discussion from both technological and social perspective. The article discusses different challenges and key issues of IoT, architecture and important application domains. Also, the article bring into light the existing literature and illustrated their contribution in different aspects of IoT. Moreover, the importance of big data and its analysis with respect to IoT has been discussed. This article would help the readers and researcher to understand the IoT and its applicability to the real world.

Introduction

The Internet of Things (IoT) is an emerging paradigm that enables the communication between electronic devices and sensors through the internet in order to facilitate our lives. IoT use smart devices and internet to provide innovative solutions to various challenges and issues related to various business, governmental and public/private industries across the world [ 1 ]. IoT is progressively becoming an important aspect of our life that can be sensed everywhere around us. In whole, IoT is an innovation that puts together extensive variety of smart systems, frameworks and intelligent devices and sensors (Fig.  1 ). Moreover, it takes advantage of quantum and nanotechnology in terms of storage, sensing and processing speed which were not conceivable beforehand [ 2 ]. Extensive research studies have been done and available in terms of scientific articles, press reports both on internet and in the form of printed materials to illustrate the potential effectiveness and applicability of IoT transformations. It could be utilized as a preparatory work before making novel innovative business plans while considering the security, assurance and interoperability.

General architecture of IoT

A great transformation can be observed in our daily routine life along with the increasing involvement of IoT devices and technology. One such development of IoT is the concept of Smart Home Systems (SHS) and appliances that consist of internet based devices, automation system for homes and reliable energy management system [ 3 ]. Besides, another important achievement of IoT is Smart Health Sensing system (SHSS). SHSS incorporates small intelligent equipment and devices to support the health of the human being. These devices can be used both indoors and outdoors to check and monitor the different health issues and fitness level or the amount of calories burned in the fitness center etc. Also, it is being used to monitor the critical health conditions in the hospitals and trauma centers as well. Hence, it has changed the entire scenario of the medical domain by facilitating it with high technology and smart devices [ 4 , 5 ]. Moreover, IoT developers and researchers are actively involved to uplift the life style of the disabled and senior age group people. IoT has shown a drastic performance in this area and has provided a new direction for the normal life of such people. As these devices and equipment are very cost effective in terms of development cost and easily available within a normal price range, hence most of the people are availing them [ 6 ]. Thanks to IoT, as they can live a normal life. Another important aspect of our life is transportation. IoT has brought up some new advancements to make it more efficient, comfortable and reliable. Intelligent sensors, drone devices are now controlling the traffic at different signalized intersections across major cities. In addition, vehicles are being launched in markets with pre-installed sensing devices that are able to sense the upcoming heavy traffic congestions on the map and may suggest you another route with low traffic congestion [ 7 ]. Therefore IoT has a lot to serve in various aspects of life and technology. We may conclude that IoT has a lot of scope both in terms of technology enhancement and facilitate the humankind.

IoT has also shown its importance and potential in the economic and industrial growth of a developing region. Also, in trade and stock exchange market, it is being considered as a revolutionary step. However, security of data and information is an important concern and highly desirable, which is a major challenging issue to deal with [ 5 ]. Internet being a largest source of security threats and cyber-attacks has opened the various doors for hackers and thus made the data and information insecure. However, IoT is committed to provide the best possible solutions to deal with security issues of data and information. Hence, the most important concern of IoT in trade and economy is security. Therefore, the development of a secure path for collaboration between social networks and privacy concerns is a hot topic in IoT and IoT developers are working hard for this.

The remaining part of the article is organized as follows: “ Literature survey ” section will provide state of art on important studies that addressed various challenges and issues in IoT. “ IoT architecture and technologies ” section discussed the IoT functional blocks, architecture in detail. In “ Major key issues and challenges of IoT ” section, important key issues and challenges of IoT is discussed. “ Major IoT applications ” section provides emerging application domains of IoT. In “ Importance of big data analytics in IoT ” section, the role and importance of big data and its analysis is discussed. Finally, the article concluded in “ Conclusions ” section.

Literature survey

IoT has a multidisciplinary vision to provide its benefit to several domains such as environmental, industrial, public/private, medical, transportation etc. Different researchers have explained the IoT differently with respect to specific interests and aspects. The potential and power of IoT can be seen in several application domains. Figure  2 illustrates few of the application domains of IoTs potentials.

Some of the potential application domains of IoT

Various important IoT projects have taken charge over the market in last few years. Some of the important IoT projects that have captured most of the market are shown in Fig.  3 . In Fig.  3 , a global distribution of these IoT projects is shown among American, European and Asia/Pacific region. It can be seen that American continent are contributing more in the health care and smart supply chain projects whereas contribution of European continent is more in the smart city projects [ 8 ].

Global distribution of IoT projects among America (USA, South America and Canada), Europe and APAC (Asia and Pacific region) [ 8 ]

Figure  4 , illustrates the global market share of IoT projects worldwide [ 8 ]. It is evident that industry, smart city, smart energy and smart vehicle based IoT projects have a big market share in comparison to others.

Global share of IoT projects across the world [ 8 ]

Smart city is one of the trendy application areas of IoT that incorporates smart homes as well. Smart home consists of IoT enabled home appliances, air-conditioning/heating system, television, audio/video streaming devices, and security systems which are communicating with each other in order to provide best comfort, security and reduced energy consumption. All this communication takes place through IoT based central control unit using Internet. The concept of smart city gained popularity in the last decade and attracted a lot of research activities [ 9 ]. The smart home business economy is about to cross the 100 billion dollars by 2022 [ 10 ]. Smart home does not only provide the in-house comfort but also benefits the house owner in cost cutting in several aspects i.e. low energy consumption will results in comparatively lower electricity bill. Besides smart homes, another category that comes within smart city is smart vehicles. Modern cars are equipped with intelligent devices and sensors that control most of the components from the headlights of the car to the engine [ 11 ]. The IoT is committed towards developing a new smart car systems that incorporates wireless communication between car-to-car and car-to-driver to ensure predictive maintenance with comfortable and safe driving experience [ 12 ].

Khajenasiri et al. [ 10 ] performed a survey on the IoT solutions for smart energy control to benefit the smart city applications. They stated that at present IoT has been deployed in very few application areas to serve the technology and people. The scope of IoT is very wide and in near future IoT is able to capture almost all application areas. They mentioned that energy saving is one of the important part of the society and IoT can assist in developing a smart energy control system that will save both energy and money. They described an IoT architecture with respect to smart city concept. The authors also discussed that one of the challenging task in achieving this is the immaturity of IoT hardware and software. They suggested that these issues must be resolved to ensure a reliable, efficient and user friendly IoT system.

Alavi et al. [ 13 ] addressed the urbanization issue in the cities. The movement of people from rural to urban atmosphere resulting in growing population of the cities. Therefore, there is a need to provide smart solutions for mobility, energy, healthcare and infrastructure. Smart city is one of the important application areas for IoT developers. It explores several issues such as traffic management, air quality management, public safety solutions, smart parking, smart lightning and smart waste collection (Fig.  5 ). They mentioned that IoT is working hard to tackle these challenging issues. The need for improved smart city infrastructure with growing urbanization has opened the doors for entrepreneurs in the field of smart city technologies. The authors concluded that IoT enabled technology is very important for the development of sustainable smart cities.

Potential IoT application areas for smart cities

Another important issue of IoT that requires attention and a lot of research is security and privacy. Weber [ 14 ] focused on these issues and suggested that a private organization availing IoT must incorporate data authentication, access control, resilience to attacks and client privacy into their business activities that would be an additional advantage. Weber suggested that in order to define global security and privacy issues, IoT developers must take into account the geographical limitations of the different countries. A generic framework needs to be designed to fit the global needs in terms of privacy and security. It is highly recommended to investigate and recognize the issues and challenges in privacy and security before developing the full fledge working IoT framework.

Later, Heer et al. [ 15 ] came up with a security issue in IP based IoT system. They mentioned that internet is backbone for the communication among devices that takes place in an IoT system. Therefore, security issues in IP based IoT systems are an important concern. In addition, security architecture should be designed considering the life cycle and capabilities of any object in the IoT system. It also includes the involvement of the trusted third party and the security protocols. The security architecture with scalability potential to serve the small-scale to large-scale things in IoT is highly desirable. The study pointed out that IoT gave rise to a new way of communication among several things across the network therefore traditional end to end internet protocol are not able to provide required support to this communication. Therefore, new protocols must be designed considering the translations at the gateways to ensure end-to-end security. Moreover, all the layers responsible for communication has their own security issues and requirements. Therefore, satisfying the requirements for one particular layers will leave the system into a vulnerable state and security should be ensured for all the layers.

Authentication and access control is another issue in IoT that needs promising solutions to strengthen the security. Liu et al. [ 16 ] brought up a solution to handle authentication and access control. Authentication is very important to verify the communicating parties to prevent the loss of confidential information. Liu et al. [ 16 ] provided an authentication scheme based on Elliptic Curve Cryptosystem and verified it on different security threats i.e. eavesdropping, man-in-the-middle attack, key control and replay attack. They claimed that there proposed schemes are able to provide better authentication and access control in IoT based communication. Later, Kothmayr et al. [ 17 ] proposed a two-way authentication scheme based of datagram transport layer security (DTLS) for IoT. The attackers over the internet are always active to steal the secured information. The proposed approach are able to provide message security, integrity, authenticity and confidentiality, memory overhead and end-to-end latency in the IoT based communication network.

Li et al. [ 18 ] proposed a dynamic approach for data centric IoT applications with respect to cloud platforms. The need of an appropriate device, software configuration and infrastructure requires efficient solutions to support massive amount of IoT applications that are running on cloud platforms. IoT developers and researchers are actively engaged in developing solutions considering both massive platforms and heterogeneous nature of IoT objects and devices. Olivier et al. [ 19 ] explained the concept of software defined networking (SDN) based architecture that performs well even if a well-defined architecture is not available. They proposed that SDN based security architecture is more flexible and efficient for IoT.

Luk et al. [ 20 ] stated that the main task of a secure sensor network (SSN) is to provide data privacy, protection from replay attacks and authentication. They discussed two popular SSN services namely TinySec [ 21 ] and ZigBee [ 22 ]. They mentioned that although both the SSN services are efficient and reliable, however, ZigBee is comparatively provides higher security but consumes high energy whereas TinySec consumes low energy but not as highly secured as ZigBee. They proposed another architecture MiniSec to support high security and low energy consumption and demonstrated its performance for the Telos platform. Yan et al. [ 23 ] stated that trust management is an important issue in IoT. Trust management helps people to understand and trust IoT services and applications without worrying about uncertainty issues and risks [ 24 ]. They investigated different issues in trust management and discussed its importance with respect to IoT developers and users.

Noura et al. [ 25 ] stated the importance of interoperability in IoT as it allows integration of devices, services from different heterogeneous platforms to provide the efficient and reliable service. Several other studies focused on the importance of interoperability and discussed several challenges that interoperability issue is facing in IoT [ 26 , 27 , 28 ]. Kim et al. [ 29 ] addressed the issue of climate change and proposed an IoT based ecological monitoring system. They mentioned that existing approaches are time consuming and required a lot of human intervention. Also, a routine visit is required to collect the information from the sensors installed at the site under investigation. Also, some information remained missing which leads to not highly accurate analysis. Therefore, IoT based framework is able to solve this problem and can provide high accuracy in analysis and prediction. Later, Wang et al. [ 30 ] shows their concern for domestic waste water treatment. They discussed several deficiencies in the process of waste water treatment and dynamic monitoring system and suggested effective solutions based on IoT. They stated that IoT can be very effective in the waste water treatment and process monitoring.

Agriculture is one of the important domain around the world. Agriculture depends on several factors i.e. geographical, ecological etc. Qiu et al. [ 31 ] stated that technology that is being used for ecosystem control is immature with low intelligence level. They mentioned that it could be a good application area for IoT developers and researchers.

Qiu et al. [ 31 ] proposed an intelligent monitoring platform framework for facility agriculture ecosystem based on IoT that consists of four layer mechanism to manage the agriculture ecosystem. Each layer is responsible for specific task and together the framework is able to achieve a better ecosystem with reduced human intervention.

Another important concern around the world is climate change due to global warming. Fang et al. [ 32 ] introduced an integrated information system (IIS) that integrates IoT, geo-informatics, cloud computing, global positioning system (GPS), geographical information system (GIS) and e-science in order to provide an effective environmental monitoring and control system. They mentioned that the proposed IIS provides improved data collection, analysis and decision making for climate control. Air pollution is another important concern worldwide. Various tools and techniques are available to air quality measures and control. Cheng et al. [ 33 ] proposed AirCloud which is a cloud based air quality and monitoring system. They deployed AirCloud and evaluated its performance using 5 months data for the continuous duration of 2 months.

Temglit et al. [ 34 ] considered Quality of Service (QoS) as an important challenge and a complex task in evaluation and selection of IoT devices, protocols and services. QoS is very important criteria to attract and gain trust of users towards IoT services and devices. They came up with an interesting distributed QoS selection approach. This approach was based on distributed constraint optimization problem and multi-agent paradigm. Further, the approach was evaluated based on several experiments under realistic distributed environments. Another important aspect of IoT is its applicability to the environmental and agriculture standards. Talavera et al. [ 35 ] focused in this direction and presented the fundamental efforts of IoT for agro-industrial and environmental aspects in a survey study. They mentioned that the efforts of IoT in these areas are noticeable. IoT is strengthening the current technology and benefiting the farmers and society. Jara et al. [ 36 ] discussed the importance of IoT based monitoring of patients health. They suggested that IoT devices and sensors with the help of internet can assist health monitoring of patients. They also proposed a framework and protocol to achieve their objective. Table 1 provides a summary of the important studies and the direction of research with a comparison of studies on certain evaluation parameters.

IoT architecture and technologies

The IoT architecture consists of five important layers that defines all the functionalities of IoT systems. These layers are perception layer, network layer, middleware layer, application layer, business layer. At the bottom of IoT architecture, perception layer exists that consists of physical devices i.e. sensors, RFID chips, barcodes etc. and other physical objects connected in IoT network. These devices collects information in order to deliver it to the network layer. Network layer works as a transmission medium to deliver the information from perception layer to the information processing system. This transmission of information may use any wired/wireless medium along with 3G/4G, Wi-Fi, Bluetooth etc. Next level layer is known as middleware layer. The main task of this layer is to process the information received from the network layer and make decisions based on the results achieved from ubiquitous computing. Next, this processed information is used by application layer for global device management. On the top of the architecture, there is a business layer which control the overall IoT system, its applications and services. The business layer visualizes the information and statistics received from the application layer and further used this knowledge to plan future targets and strategies. Furthermore, the IoT architectures can be modified according to the need and application domain [ 19 , 20 , 37 ]. Besides layered framework, IoT system consists of several functional blocks that supports various IoT activities such as sensing mechanism, authentication and identification, control and management [ 38 ]. Figure  6 illustrates such functional blocks of IoT architecture.

A generic function module of IoT system

There are several important functional blocks responsible for I/O operations, connectivity issues, processing, audio/video monitoring and storage management. All these functional block together incorporates an efficient IoT system which are important for optimum performance. Although, there are several reference architectures proposed with the technical specifications, but these are still far from the standard architecture that is suitable for global IoT [ 39 ]. Therefore, a suitable architecture is still needsvk to be designed that could satisfy the global IoT needs. The generic working structure of IoT system is shown in Fig.  7 . Figure  7 shows a dependency of IoT on particular application parameters. IoT gateways have an important role in IoT communication as it allows connectivity between IoT servers and IoT devices related to several applications [ 40 ].

Working structure of IoT

Scalability, modularity, interoperability and openness are the key design issues for an efficient IoT architecture in a heterogenous environment. The IoT architecture must be designed with an objective to fulfil the requirements of cross domain interactions, multi-system integration with the potential of simple and scalable management functionalities, big data analytics and storage, and user friendly applications. Also, the architecture should be able to scaleup the functionality and add some intelligence and automation among the IoT devices in the system.

Moreover, increasing amount of massive data being generated through the communication between IoT sensors and devices is a new challenge. Therefore, an efficient architecture is required to deal with massive amount of streaming data in IoT system. Two popular IoT system architectures are cloud and fog/edge computing that supports with the handling, monitoring and analysis of huge amount of data in IoT systems. Therefore, a modern IoT architecture can be defined as a 4 stage architecture as shown in Fig.  8 .

Four stage IoT architecture to deal with massive data

In stage 1 of the architecture, sensors and actuators plays an important role. Real world is comprised of environment, humans, animals, electronic gadgets, smart vehicles, and buildings etc. Sensors detect the signals and data flow from these real world entities and transforms into data which could further be used for analysis. Moreover, actuators is able to intervene the reality i.e. to control the temperature of the room, to slow down the vehicle speed, to turn off the music and light etc. Therefore, stage 1 assist in collecting data from real world which could be useful for further analysis. Stage 2 is responsible to collaborate with sensors and actuators along with gateways and data acquisition systems. In this stage, massive amount of data generated in stage 1 is aggregated and optimized in a structured way suitable for processing. Once the massive amount of data is aggregated and structured then it is ready to be passed to stage 3 which is edge computing. Edge computing can be defined as an open architecture in distributed fashion which allows use of IoT technologies and massive computing power from different locations worldwide. It is very powerful approach for streaming data processing and thus suitable for IoT systems. In stage 3, edge computing technologies deals with massive amount of data and provides various functionalities such as visualization, integration of data from other sources, analysis using machine learning methods etc. The last stage comprises of several important activities such as in depth processing and analysis, sending feedback to improve the precision and accuracy of the entire system. Everything at this stage will be performed on cloud server or data centre. Big data framework such as Hadoop and Spark may be utilized to handle this large streaming data and machine learning approaches can be used to develop better prediction models which could help in a more accurate and reliable IoT system to meet the demand of present time.

Major key issues and challenges of IoT

The involvement of IoT based systems in all aspects of human lives and various technologies involved in data transfer between embedded devices made it complex and gave rise to several issues and challenges. These issues are also a challenge for the IoT developers in the advanced smart tech society. As technology is growing, challenges and need for advanced IoT system is also growing. Therefore, IoT developers need to think of new issues arising and should provide solutions for them.

Security and privacy issues

One of the most important and challenging issues in the IoT is the security and privacy due to several threats, cyber attacks, risks and vulnerabilities [ 41 ]. The issues that give rise to device level privacy are insufficient authorization and authentication, insecure software, firmware, web interface and poor transport layer encryption [ 42 ]. Security and privacy issues are very important parameters to develop confidence in IoT Systems with respect to various aspects [ 43 ]. Security mechanisms must be embedded at every layer of IoT architecture to prevent security threats and attacks [ 23 ]. Several protocols are developed and efficiently deployed on every layer of communication channel to ensure the security and privacy in IoT based systems [ 44 , 45 ]. Secure Socket Layer (SSL) and Datagram Transport Layer Security (DTLS) are one of the cryptographic protocols that are implemented between transport and application layer to provide security solutions in various IoT systems [ 44 ]. However, some IoT applications require different methods to ensure the security in communication between IoT devices. Besides this, if communication takes place using wireless technologies within the IoT system, it becomes more vulnerable to security risks. Therefore, certain methods should be deployed to detect malicious actions and for self healing or recovery. Privacy on the other hand is another important concern which allows users to feel secure and comfortable while using IoT solutions. Therefore, it is required to maintain the authorization and authentication over a secure network to establish the communication between trusted parties [ 46 ]. Another issue is the different privacy policies for different objects communicating within the IoT system. Therefore, each object should be able to verify the privacy policies of other objects in IoT system before transmitting the data.

Interoperability/standard issues

Interoperability is the feasibility to exchange the information among different IoT devices and systems. This exchange of information does not rely on the deployed software and hardware. The interoperability issue arises due to the heterogeneous nature of different technology and solutions used for IoT development. The four interoperability levels are technical, semantic, syntactic and organizational [ 47 ]. Various functionalities are being provided by IoT systems to improve the interoperability that ensures communication between different objects in a heterogeneous environment. Additionally, it is possible to merge different IoT platforms based on their functionalities to provide various solutions for IoT users [ 48 ]. Considering interoperability an important issue, researchers approved several solutions that are also know as interoperability handling approaches [ 49 ]. These solutions could be adapaters/gateways based, virtual networks/overlay based, service oriented architecture based etc. Although interoperability handling approaches ease some pressure on IoT systems but there are still certain challenges remain with interoperability that could be a scope for future studies [ 25 ].

Ethics, law and regulatory rights

Another issue for IoT developers is the ethics, law and regulatory rights. There are certain rules and regulations to maintain the standard, moral values and to prevent the people from violating them. Ethics and law are very similar term with the only difference is that ethics are standards that people believes and laws are certain restrictions decided by the government. However, both ethics and laws are designed to maintain the standard, quality and prevent people from illegal use. With the development of IoT, several real life problems are solved but it has also given rise to critical ethical and legal challenges [ 50 ]. Data security, privacy protection, trust and safety, data usability are some of those challenges. It has also been observed that majority of IoT users are supporting government norms and regulations with respect to data protection, privacy and safety due to the lack of trust in IoT devices. Therefore, this issue must be taken into consideration to maintain and improve the trust among people for the use of IoT devices and systems.

Scalability, availability and reliability

A system is scalable if it is possible to add new services, equipments and devices without degrading its performance. The main issue with IoT is to support a large number of devices with different memory, processing, storage power and bandwidth [ 28 ]. Another important issue that must be taken into consideration is the availability. Scalability and availability both should be deployed together in the layered framework of IoT. A great example of scalability is cloud based IoT systems which provide sufficient support to scale the IoT network by adding up new devices, storage and processing power as required.

However, this global distributed IoT network gives rise to a new research paradigm to develop a smooth IoT framework that satisfy global needs [ 51 ]. Another key challenge is the availability of resources to the authentic objects regardless of their location and time of the requirement. In a distributed fashion, several small IoT networks are timely attached to the global IoT platforms to utilize their resources and services. Therefore, availability is an important concern [ 52 ]. Due to the use of different data transmission channels i.e. satellite communication, some services and availability of resources may be interrupted. Therefore, an independent and reliable data transmission channel is required for uninterrupted availability of resources and services.

Quality of Service (QoS)

Quality of Service (QoS) is another important factor for IoT. QoS can be defined as a measure to evaluate the quality, efficiency and performance of IoT devices, systems and architecture [ 34 ]. The important and required QoS metrics for IoT applications are reliability, cost, energy consumption, security, availability and service time [ 53 ]. A smarter IoT ecosystem must fulfill the requirements of QoS standards. Also, to ensure the reliability of any IoT service and device, its QoS metrics must be defined first. Further, users may also be able to specifiy their needs and requirements accordingly. Several approaches can be deployed for QoS assessment, however as mentioned by White et al. [ 54 ] there is a trade-off between quality factors and approaches. Therefore, good quality models must be deployed to overcome this trade-off. There are certain good quality models available in literature such as ISO/IEC25010 [ 55 ] and OASIS-WSQM [ 56 ] which can be used to evaluate the approaches used for QoS assessment. These models provides a wide range of quality factors that is quite sufficient for QoS assessment for IoT services. Table  2 summarizes the different studies with respect to IoT key challenges and issues discussed above.

Major IoT applications

Emerging economy, environmental and health-care.

IoT is completely devoted to provide emerging public and financial benefits and development to the society and people. This includes a wide range of public facilities i.e. economic development, water quality maintenance, well-being, industrialization etc. Overall, IoT is working hard to accomplish the social, health and economic goals of United Nations advancement step. Environmental sustainability is another important concern. IoT developers must be concerned about environmental impact of the IoT systems and devices to overcome the negative impact [ 48 ]. Energy consumption by IoT devices is one of the challenges related to environmental impact. Energy consumption is increasing at a high rate due to internet enabled services and edge cutting devices. This area needs research for the development of high quality materials in order to create new IoT devices with lower energy consumption rate. Also, green technologies can be adopted to create efficient energy efficient devices for future use. It is not only environmental friendly but also advantageous for human health. Researchers and engineers are engaged in developing highly efficient IoT devices to monitor several health issues such as diabetes, obesity or depression [ 57 ]. Several issues related to environment, energy and healthcare are considered by several studies.

Smart city, transport and vehicles

IoT is transforming the traditional civil structure of the society into high tech structure with the concept of smart city, smart home and smart vehicles and transport. Rapid improvements are being done with the help of supporting technologies such as machine learning, natural language processing to understand the need and use of technology at home [ 58 ]. Various technologies such as cloud server technology, wireless sensor networks that must be used with IoT servers to provide an efficient smart city. Another important issue is to think about environmental aspect of smart city. Therefore, energy efficient technologies and Green technologies should also be considered for the design and planning of smart city infrastructure. Further, smart devices which are being incorporated into newly launched vehicles are able to detect traffic congestions on the road and thus can suggest an optimum alternate route to the driver. This can help to lower down the congestion in the city. Furthermore, smart devices with optimum cost should be designed to be incorporated in all range vehicles to monitor the activity of engine. IoT is also very effective in maintaining the vehicle’s health. Self driving cars have the potential to communicate with other self driving vehicles by the means of intelligent sensors. This would make the traffic flow smoother than human-driven cars who used to drive in a stop and go manner. This procedure will take time to be implemented all over the world. Till the time, IoT devices can help by sensing traffic congestion ahead and can take appropriate actions. Therefore, a transport manufacturing company should incorporate IoT devices into their manufactured vehicles to provide its advantage to the society.

Agriculture and industry automation

The world’s growing population is estimated to reach approximate 10 billion by 2050. Agriculture plays an important role in our lives. In order to feed such a massive population, we need to advance the current agriculture approaches. Therefore, there is a need to combine agriculture with technology so that the production can be improved in an efficient way. Greenhouse technology is one of the possible approaches in this direction. It provides a way to control the environmental parameters in order to improve the production. However, manual control of this technology is less effective, need manual efforts and cost, and results in energy loss and less production. With the advancement of IoT, smart devices and sensors makes it easier to control the climate inside the chamber and monitor the process which results in energy saving and improved production (Fig.  9 ). Automatization of industries is another advantage of IoT. IoT has been providing game changing solutions for factory digitalization, inventory management, quality control, logistics and supply chain optimization and management.

A working structure of IoT system in agriculture production

Importance of big data analytics in IoT

An IoT system comprises of a huge number of devices and sensors that communicates with each other. With the extensive growth and expansion of IoT network, the number of these sensors and devices are increasing rapidly. These devices communicate with each other and transfer a massive amount of data over internet. This data is very huge and streaming every second and thus qualified to be called as big data. Continuous expansion of IoT based networks gives rise to complex issue such as management and collection of data, storage and processing and analytics. IoT big data framework for smart buildings is very useful to deal with several issues of smart buildings such as managing oxygen level, to measure the smoke/hazardous gases and luminosity [ 59 ]. Such framework is capable to collect the data from the sensors installed in the buildings and performs data analytics for decision making. Moreover, industrial production can be improved using an IoT based cyber physical system that is equipped with an information analysis and knowledge acquisition techniques [ 60 ]. Traffic congestion is an important issue with smart cities. The real time traffic information can be collected through IoT devices and sensors installed in traffic signals and this information can be analyzed in an IoT based traffic management system [ 61 ]. In healthcare analysis, the IoT sensors used with patients generate a lot of information about the health condition of patients every second. This large amount of information needs to be integrated at one database and must be processed in real time to take quick decision with high accuracy and big data technology is the best solution for this job [ 62 ]. IoT along with big data analytics can also help to transform the traditional approaches used in manufacturing industries into the modern one [ 63 ]. The sensing devices generates information which can be analyzed using big data approaches and may help in various decision making tasks. Furthermore, use of cloud computing and analytics can benefit the energy development and conservation with reduced cost and customer satisfaction [ 64 ]. IoT devices generate a huge amount of streaming data which needs to be stored effectively and needs further analysis for decision making in real time. Deep learning is very effective to deal with such a large information and can provide results with high accuracy [ 65 ]. Therefore, IoT, Big data analytics and Deep learning together is very important to develop a high tech society.

Conclusions

Recent advancements in IoT have drawn attention of researchers and developers worldwide. IoT developers and researchers are working together to extend the technology on large scale and to benefit the society to the highest possible level. However, improvements are possible only if we consider the various issues and shortcomings in the present technical approaches. In this survey article, we presented several issues and challenges that IoT developer must take into account to develop an improved model. Also, important application areas of IoT is also discussed where IoT developers and researchers are engaged. As IoT is not only providing services but also generates a huge amount of data. Hence, the importance of big data analytics is also discussed which can provide accurate decisions that could be utilized to develop an improved IoT system.

Availability of data and materials

Not applicable.

Abbreviations

Internet of Things

Quality of Service

Web of Things

Cloud of Things

Smart Home System

Smart Health Sensing System

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This work was financially supported by the Ministry of Education and Science of Russian Federation (government order 2.7905.2017/8.9).

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Kumar, S., Tiwari, P. & Zymbler, M. Internet of Things is a revolutionary approach for future technology enhancement: a review. J Big Data 6 , 111 (2019). https://doi.org/10.1186/s40537-019-0268-2

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Study and Investigation on 5G Technology: A Systematic Review

Ramraj dangi.

1 School of Computing Science and Engineering, VIT University Bhopal, Bhopal 466114, India; [email protected] (R.D.); [email protected] (P.L.)

Praveen Lalwani

Gaurav choudhary.

2 Department of Applied Mathematics and Computer Science, Technical University of Denmark, 2800 Lyngby, Denmark; moc.liamg@7777yrahduohcvaruag

3 Department of Information Security Engineering, Soonchunhyang University, Asan-si 31538, Korea

Giovanni Pau

4 Faculty of Engineering and Architecture, Kore University of Enna, 94100 Enna, Italy; [email protected]

Associated Data

Not applicable.

In wireless communication, Fifth Generation (5G) Technology is a recent generation of mobile networks. In this paper, evaluations in the field of mobile communication technology are presented. In each evolution, multiple challenges were faced that were captured with the help of next-generation mobile networks. Among all the previously existing mobile networks, 5G provides a high-speed internet facility, anytime, anywhere, for everyone. 5G is slightly different due to its novel features such as interconnecting people, controlling devices, objects, and machines. 5G mobile system will bring diverse levels of performance and capability, which will serve as new user experiences and connect new enterprises. Therefore, it is essential to know where the enterprise can utilize the benefits of 5G. In this research article, it was observed that extensive research and analysis unfolds different aspects, namely, millimeter wave (mmWave), massive multiple-input and multiple-output (Massive-MIMO), small cell, mobile edge computing (MEC), beamforming, different antenna technology, etc. This article’s main aim is to highlight some of the most recent enhancements made towards the 5G mobile system and discuss its future research objectives.

1. Introduction

Most recently, in three decades, rapid growth was marked in the field of wireless communication concerning the transition of 1G to 4G [ 1 , 2 ]. The main motto behind this research was the requirements of high bandwidth and very low latency. 5G provides a high data rate, improved quality of service (QoS), low-latency, high coverage, high reliability, and economically affordable services. 5G delivers services categorized into three categories: (1) Extreme mobile broadband (eMBB). It is a nonstandalone architecture that offers high-speed internet connectivity, greater bandwidth, moderate latency, UltraHD streaming videos, virtual reality and augmented reality (AR/VR) media, and many more. (2) Massive machine type communication (eMTC), 3GPP releases it in its 13th specification. It provides long-range and broadband machine-type communication at a very cost-effective price with less power consumption. eMTC brings a high data rate service, low power, extended coverage via less device complexity through mobile carriers for IoT applications. (3) ultra-reliable low latency communication (URLLC) offers low-latency and ultra-high reliability, rich quality of service (QoS), which is not possible with traditional mobile network architecture. URLLC is designed for on-demand real-time interaction such as remote surgery, vehicle to vehicle (V2V) communication, industry 4.0, smart grids, intelligent transport system, etc. [ 3 ].

1.1. Evolution from 1G to 5G

First generation (1G): 1G cell phone was launched between the 1970s and 80s, based on analog technology, which works just like a landline phone. It suffers in various ways, such as poor battery life, voice quality, and dropped calls. In 1G, the maximum achievable speed was 2.4 Kbps.

Second Generation (2G): In 2G, the first digital system was offered in 1991, providing improved mobile voice communication over 1G. In addition, Code-Division Multiple Access (CDMA) and Global System for Mobile (GSM) concepts were also discussed. In 2G, the maximum achievable speed was 1 Mpbs.

Third Generation (3G): When technology ventured from 2G GSM frameworks into 3G universal mobile telecommunication system (UMTS) framework, users encountered higher system speed and quicker download speed making constant video calls. 3G was the first mobile broadband system that was formed to provide the voice with some multimedia. The technology behind 3G was high-speed packet access (HSPA/HSPA+). 3G used MIMO for multiplying the power of the wireless network, and it also used packet switching for fast data transmission.

Fourth Generation (4G): It is purely mobile broadband standard. In digital mobile communication, it was observed information rate that upgraded from 20 to 60 Mbps in 4G [ 4 ]. It works on LTE and WiMAX technologies, as well as provides wider bandwidth up to 100 Mhz. It was launched in 2010.

Fourth Generation LTE-A (4.5G): It is an advanced version of standard 4G LTE. LTE-A uses MIMO technology to combine multiple antennas for both transmitters as well as a receiver. Using MIMO, multiple signals and multiple antennas can work simultaneously, making LTE-A three times faster than standard 4G. LTE-A offered an improved system limit, decreased deferral in the application server, access triple traffic (Data, Voice, and Video) wirelessly at any time anywhere in the world.LTE-A delivers speeds of over 42 Mbps and up to 90 Mbps.

Fifth Generation (5G): 5G is a pillar of digital transformation; it is a real improvement on all the previous mobile generation networks. 5G brings three different services for end user like Extreme mobile broadband (eMBB). It offers high-speed internet connectivity, greater bandwidth, moderate latency, UltraHD streaming videos, virtual reality and augmented reality (AR/VR) media, and many more. Massive machine type communication (eMTC), it provides long-range and broadband machine-type communication at a very cost-effective price with less power consumption. eMTC brings a high data rate service, low power, extended coverage via less device complexity through mobile carriers for IoT applications. Ultra-reliable low latency communication (URLLC) offers low-latency and ultra-high reliability, rich quality of service (QoS), which is not possible with traditional mobile network architecture. URLLC is designed for on-demand real-time interaction such as remote surgery, vehicle to vehicle (V2V) communication, industry 4.0, smart grids, intelligent transport system, etc. 5G faster than 4G and offers remote-controlled operation over a reliable network with zero delays. It provides down-link maximum throughput of up to 20 Gbps. In addition, 5G also supports 4G WWWW (4th Generation World Wide Wireless Web) [ 5 ] and is based on Internet protocol version 6 (IPv6) protocol. 5G provides unlimited internet connection at your convenience, anytime, anywhere with extremely high speed, high throughput, low-latency, higher reliability and scalability, and energy-efficient mobile communication technology [ 6 ]. 5G mainly divided in two parts 6 GHz 5G and Millimeter wave(mmWave) 5G.

6 GHz is a mid frequency band which works as a mid point between capacity and coverage to offer perfect environment for 5G connectivity. 6 GHz spectrum will provide high bandwidth with improved network performance. It offers continuous channels that will reduce the need for network densification when mid-band spectrum is not available and it makes 5G connectivity affordable at anytime, anywhere for everyone.

mmWave is an essential technology of 5G network which build high performance network. 5G mmWave offer diverse services that is why all network providers should add on this technology in their 5G deployment planning. There are lots of service providers who deployed 5G mmWave, and their simulation result shows that 5G mmwave is a far less used spectrum. It provides very high speed wireless communication and it also offers ultra-wide bandwidth for next generation mobile network.

The evolution of wireless mobile technologies are presented in Table 1 . The abbreviations used in this paper are mentioned in Table 2 .

Summary of Mobile Technology.

Table of Notations and Abbreviations.

1.2. Key Contributions

The objective of this survey is to provide a detailed guide of 5G key technologies, methods to researchers, and to help with understanding how the recent works addressed 5G problems and developed solutions to tackle the 5G challenges; i.e., what are new methods that must be applied and how can they solve problems? Highlights of the research article are as follows.

• This survey focused on the recent trends and development in the era of 5G and novel contributions by the researcher community and discussed technical details on essential aspects of the 5G advancement.
• In this paper, the evolution of the mobile network from 1G to 5G is presented. In addition, the growth of mobile communication under different attributes is also discussed.
• This paper covers the emerging applications and research groups working on 5G & different research areas in 5G wireless communication network with a descriptive taxonomy.
• This survey discusses the current vision of the 5G networks, advantages, applications, key technologies, and key features. Furthermore, machine learning prospects are also explored with the emerging requirements in the 5G era. The article also focused on technical aspects of 5G IoT Based approaches and optimization techniques for 5G.
• we provide an extensive overview and recent advancement of emerging technologies of 5G mobile network, namely, MIMO, Non-Orthogonal Multiple Access (NOMA), mmWave, Internet of Things (IoT), Machine Learning (ML), and optimization. Also, a technical summary is discussed by highlighting the context of current approaches and corresponding challenges.
• Security challenges and considerations while developing 5G technology are discussed.
• Finally, the paper concludes with the future directives.

The existing survey focused on architecture, key concepts, and implementation challenges and issues. In contrast, this survey covers the state-of-the-art techniques as well as corresponding recent novel developments by researchers. Various recent significant papers are discussed with the key technologies accelerating the development and production of 5G products.

2. Existing Surveys and Their Applicability

In this paper, a detailed survey on various technologies of 5G networks is presented. Various researchers have worked on different technologies of 5G networks. In this section, Table 3 gives a tabular representation of existing surveys of 5G networks. Massive MIMO, NOMA, small cell, mmWave, beamforming, and MEC are the six main pillars that helped to implement 5G networks in real life.

A comparative overview of existing surveys on different technologies of 5G networks.

2.1. Limitations of Existing Surveys

The existing survey focused on architecture, key concepts, and implementation challenges and issues. The numerous current surveys focused on various 5G technologies with different parameters, and the authors did not cover all the technologies of the 5G network in detail with challenges and recent advancements. Few authors worked on MIMO (Non-Orthogonal Multiple Access) NOMA, MEC, small cell technologies. In contrast, some others worked on beamforming, Millimeter-wave (mmWave). But the existing survey did not cover all the technologies of the 5G network from a research and advancement perspective. No detailed survey is available in the market covering all the 5G network technologies and currently published research trade-offs. So, our main aim is to give a detailed study of all the technologies working on the 5G network. In contrast, this survey covers the state-of-the-art techniques as well as corresponding recent novel developments by researchers. Various recent significant papers are discussed with the key technologies accelerating the development and production of 5G products. This survey article collected key information about 5G technology and recent advancements, and it can be a kind of a guide for the reader. This survey provides an umbrella approach to bring multiple solutions and recent improvements in a single place to accelerate the 5G research with the latest key enabling solutions and reviews. A systematic layout representation of the survey in Figure 1 . We provide a state-of-the-art comparative overview of the existing surveys on different technologies of 5G networks in Table 3 .

Systematic layout representation of survey.

2.2. Article Organization

This article is organized under the following sections. Section 2 presents existing surveys and their applicability. In Section 3 , the preliminaries of 5G technology are presented. In Section 4 , recent advances of 5G technology based on Massive MIMO, NOMA, Millimeter Wave, 5G with IoT, machine learning for 5G, and Optimization in 5G are provided. In Section 5 , a description of novel 5G features over 4G is provided. Section 6 covered all the security concerns of the 5G network. Section 7 , 5G technology based on above-stated challenges summarize in tabular form. Finally, Section 8 and Section 9 conclude the study, which paves the path for future research.

3. Preliminary Section

3.1. emerging 5g paradigms and its features.

5G provides very high speed, low latency, and highly salable connectivity between multiple devices and IoT worldwide. 5G will provide a very flexible model to develop a modern generation of applications and industry goals [ 26 , 27 ]. There are many services offered by 5G network architecture are stated below:

Massive machine to machine communications: 5G offers novel, massive machine-to-machine communications [ 28 ], also known as the IoT [ 29 ], that provide connectivity between lots of machines without any involvement of humans. This service enhances the applications of 5G and provides connectivity between agriculture, construction, and industries [ 30 ].

Ultra-reliable low latency communications (URLLC): This service offers real-time management of machines, high-speed vehicle-to-vehicle connectivity, industrial connectivity and security principles, and highly secure transport system, and multiple autonomous actions. Low latency communications also clear up a different area where remote medical care, procedures, and operation are all achievable [ 31 ].

Enhanced mobile broadband: Enhance mobile broadband is an important use case of 5G system, which uses massive MIMO antenna, mmWave, beamforming techniques to offer very high-speed connectivity across a wide range of areas [ 32 ].

For communities: 5G provides a very flexible internet connection between lots of machines to make smart homes, smart schools, smart laboratories, safer and smart automobiles, and good health care centers [ 33 ].

For businesses and industry: As 5G works on higher spectrum ranges from 24 to 100 GHz. This higher frequency range provides secure low latency communication and high-speed wireless connectivity between IoT devices and industry 4.0, which opens a market for end-users to enhance their business models [ 34 ].

New and Emerging technologies: As 5G came up with many new technologies like beamforming, massive MIMO, mmWave, small cell, NOMA, MEC, and network slicing, it introduced many new features to the market. Like virtual reality (VR), users can experience the physical presence of people who are millions of kilometers away from them. Many new technologies like smart homes, smart workplaces, smart schools, smart sports academy also came into the market with this 5G Mobile network model [ 35 ].

3.2. Commercial Service Providers of 5G

5G provides high-speed internet browsing, streaming, and downloading with very high reliability and low latency. 5G network will change your working style, and it will increase new business opportunities and provide innovations that we cannot imagine. This section covers top service providers of 5G network [ 36 , 37 ].

Ericsson: Ericsson is a Swedish multinational networking and telecommunications company, investing around 25.62 billion USD in 5G network, which makes it the biggest telecommunication company. It claims that it is the only company working on all the continents to make the 5G network a global standard for the next generation wireless communication. Ericsson developed the first 5G radio prototype that enables the operators to set up the live field trials in their network, which helps operators understand how 5G reacts. It plays a vital role in the development of 5G hardware. It currently provides 5G services in over 27 countries with content providers like China Mobile, GCI, LGU+, AT&T, Rogers, and many more. It has 100 commercial agreements with different operators as of 2020.

Verizon: It is American multinational telecommunication which was founded in 1983. Verizon started offering 5G services in April 2020, and by December 2020, it has actively provided 5G services in 30 cities of the USA. They planned that by the end of 2021, they would deploy 5G in 30 more new cities. Verizon deployed a 5G network on mmWave, a very high band spectrum between 30 to 300 GHz. As it is a significantly less used spectrum, it provides very high-speed wireless communication. MmWave offers ultra-wide bandwidth for next-generation mobile networks. MmWave is a faster and high-band spectrum that has a limited range. Verizon planned to increase its number of 5G cells by 500% by 2020. Verizon also has an ultra wide-band flagship 5G service which is the best 5G service that increases the market price of Verizon.

Nokia: Nokia is a Finnish multinational telecommunications company which was founded in 1865. Nokia is one of the companies which adopted 5G technology very early. It is developing, researching, and building partnerships with various 5G renders to offer 5G communication as soon as possible. Nokia collaborated with Deutsche Telekom and Hamburg Port Authority and provided them 8000-hectare site for their 5G MoNArch project. Nokia is the only company that supplies 5G technology to all the operators of different countries like AT&T, Sprint, T-Mobile US and Verizon in the USA, Korea Telecom, LG U+ and SK Telecom in South Korea and NTT DOCOMO, KDDI, and SoftBank in Japan. Presently, Nokia has around 150+ agreements and 29 live networks all over the world. Nokia is continuously working hard on 5G technology to expand 5G networks all over the globe.

AT&T: AT&T is an American multinational company that was the first to deploy a 5G network in reality in 2018. They built a gigabit 5G network connection in Waco, TX, Kalamazoo, MI, and South Bend to achieve this. It is the first company that archives 1–2 gigabit per second speed in 2019. AT&T claims that it provides a 5G network connection among 225 million people worldwide by using a 6 GHz spectrum band.

T-Mobile: T-Mobile US (TMUS) is an American wireless network operator which was the first service provider that offers a real 5G nationwide network. The company knew that high-band 5G was not feasible nationwide, so they used a 600 MHz spectrum to build a significant portion of its 5G network. TMUS is planning that by 2024 they will double the total capacity and triple the full 5G capacity of T-Mobile and Sprint combined. The sprint buyout is helping T-Mobile move forward the company’s current market price to 129.98 USD.

Samsung: Samsung started their research in 5G technology in 2011. In 2013, Samsung successfully developed the world’s first adaptive array transceiver technology operating in the millimeter-wave Ka bands for cellular communications. Samsung provides several hundred times faster data transmission than standard 4G for core 5G mobile communication systems. The company achieved a lot of success in the next generation of technology, and it is considered one of the leading companies in the 5G domain.

Qualcomm: Qualcomm is an American multinational corporation in San Diego, California. It is also one of the leading company which is working on 5G chip. Qualcomm’s first 5G modem chip was announced in October 2016, and a prototype was demonstrated in October 2017. Qualcomm mainly focuses on building products while other companies talk about 5G; Qualcomm is building the technologies. According to one magazine, Qualcomm was working on three main areas of 5G networks. Firstly, radios that would use bandwidth from any network it has access to; secondly, creating more extensive ranges of spectrum by combining smaller pieces; and thirdly, a set of services for internet applications.

ZTE Corporation: ZTE Corporation was founded in 1985. It is a partially Chinese state-owned technology company that works in telecommunication. It was a leading company that worked on 4G LTE, and it is still maintaining its value and doing research and tests on 5G. It is the first company that proposed Pre5G technology with some series of solutions.

NEC Corporation: NEC Corporation is a Japanese multinational information technology and electronics corporation headquartered in Minato, Tokyo. ZTE also started their research on 5G, and they introduced a new business concept. NEC’s main aim is to develop 5G NR for the global mobile system and create secure and intelligent technologies to realize 5G services.

Cisco: Cisco is a USA networking hardware company that also sleeves up for 5G network. Cisco’s primary focus is to support 5G in three ways: Service—enable 5G services faster so all service providers can increase their business. Infrastructure—build 5G-oriented infrastructure to implement 5G more quickly. Automation—make a more scalable, flexible, and reliable 5G network. The companies know the importance of 5G, and they want to connect more than 30 billion devices in the next couple of years. Cisco intends to work on network hardening as it is a vital part of 5G network. Cisco used AI with deep learning to develop a 5G Security Architecture, enabling Secure Network Transformation.

3.3. 5G Research Groups

Many research groups from all over the world are working on a 5G wireless mobile network [ 38 ]. These groups are continuously working on various aspects of 5G. The list of those research groups are presented as follows: 5GNOW (5th Generation Non-Orthogonal Waveform for Asynchronous Signaling), NEWCOM (Network of Excellence in Wireless Communication), 5GIC (5G Innovation Center), NYU (New York University) Wireless, 5GPPP (5G Infrastructure Public-Private Partnership), EMPHATIC (Enhanced Multi-carrier Technology for Professional Adhoc and Cell-Based Communication), ETRI(Electronics and Telecommunication Research Institute), METIS (Mobile and wireless communication Enablers for the Twenty-twenty Information Society) [ 39 ]. The various research groups along with the research area are presented in Table 4 .

Research groups working on 5G mobile networks.

3.4. 5G Applications

5G is faster than 4G and offers remote-controlled operation over a reliable network with zero delays. It provides down-link maximum throughput of up to 20 Gbps. In addition, 5G also supports 4G WWWW (4th Generation World Wide Wireless Web) [ 5 ] and is based on Internet protocol version 6 (IPv6) protocol. 5G provides unlimited internet connection at your convenience, anytime, anywhere with extremely high speed, high throughput, low-latency, higher reliability, greater scalablility, and energy-efficient mobile communication technology [ 6 ].

There are lots of applications of 5G mobile network are as follows:

• High-speed mobile network: 5G is an advancement on all the previous mobile network technologies, which offers very high speed downloading speeds 0 of up to 10 to 20 Gbps. The 5G wireless network works as a fiber optic internet connection. 5G is different from all the conventional mobile transmission technologies, and it offers both voice and high-speed data connectivity efficiently. 5G offers very low latency communication of less than a millisecond, useful for autonomous driving and mission-critical applications. 5G will use millimeter waves for data transmission, providing higher bandwidth and a massive data rate than lower LTE bands. As 5 Gis a fast mobile network technology, it will enable virtual access to high processing power and secure and safe access to cloud services and enterprise applications. Small cell is one of the best features of 5G, which brings lots of advantages like high coverage, high-speed data transfer, power saving, easy and fast cloud access, etc. [ 40 ].
• Entertainment and multimedia: In one analysis in 2015, it was found that more than 50 percent of mobile internet traffic was used for video downloading. This trend will surely increase in the future, which will make video streaming more common. 5G will offer High-speed streaming of 4K videos with crystal clear audio, and it will make a high definition virtual world on your mobile. 5G will benefit the entertainment industry as it offers 120 frames per second with high resolution and higher dynamic range video streaming, and HD TV channels can also be accessed on mobile devices without any interruptions. 5G provides low latency high definition communication so augmented reality (AR), and virtual reality (VR) will be very easily implemented in the future. Virtual reality games are trendy these days, and many companies are investing in HD virtual reality games. The 5G network will offer high-speed internet connectivity with a better gaming experience [ 41 ].
• Smart homes : smart home appliances and products are in demand these days. The 5G network makes smart homes more real as it offers high-speed connectivity and monitoring of smart appliances. Smart home appliances are easily accessed and configured from remote locations using the 5G network as it offers very high-speed low latency communication.
• Smart cities: 5G wireless network also helps develop smart cities applications such as automatic traffic management, weather update, local area broadcasting, energy-saving, efficient power supply, smart lighting system, water resource management, crowd management, emergency control, etc.
• Industrial IoT: 5G wireless technology will provide lots of features for future industries such as safety, process tracking, smart packing, shipping, energy efficiency, automation of equipment, predictive maintenance, and logistics. 5G smart sensor technology also offers smarter, safer, cost-effective, and energy-saving industrial IoT operations.
• Smart Farming: 5G technology will play a crucial role in agriculture and smart farming. 5G sensors and GPS technology will help farmers track live attacks on crops and manage them quickly. These smart sensors can also be used for irrigation, pest, insect, and electricity control.
• Autonomous Driving: The 5G wireless network offers very low latency high-speed communication, significant for autonomous driving. It means self-driving cars will come to real life soon with 5G wireless networks. Using 5G autonomous cars can easily communicate with smart traffic signs, objects, and other vehicles running on the road. 5G’s low latency feature makes self-driving more real as every millisecond is essential for autonomous vehicles, decision-making is done in microseconds to avoid accidents.
• Healthcare and mission-critical applications: 5G technology will bring modernization in medicine where doctors and practitioners can perform advanced medical procedures. The 5G network will provide connectivity between all classrooms, so attending seminars and lectures will be easier. Through 5G technology, patients can connect with doctors and take their advice. Scientists are building smart medical devices which can help people with chronic medical conditions. The 5G network will boost the healthcare industry with smart devices, the internet of medical things, smart sensors, HD medical imaging technologies, and smart analytics systems. 5G will help access cloud storage, so accessing healthcare data will be very easy from any location worldwide. Doctors and medical practitioners can easily store and share large files like MRI reports within seconds using the 5G network.
• Satellite Internet: In many remote areas, ground base stations are not available, so 5G will play a crucial role in providing connectivity in such areas. The 5G network will provide connectivity using satellite systems, and the satellite system uses a constellation of multiple small satellites to provide connectivity in urban and rural areas across the world.

4. 5G Technologies

This section describes recent advances of 5G Massive MIMO, 5G NOMA, 5G millimeter wave, 5G IOT, 5G with machine learning, and 5G optimization-based approaches. In addition, the summary is also presented in each subsection that paves the researchers for the future research direction.

4.1. 5G Massive MIMO

Multiple-input-multiple-out (MIMO) is a very important technology for wireless systems. It is used for sending and receiving multiple signals simultaneously over the same radio channel. MIMO plays a very big role in WI-FI, 3G, 4G, and 4G LTE-A networks. MIMO is mainly used to achieve high spectral efficiency and energy efficiency but it was not up to the mark MIMO provides low throughput and very low reliable connectivity. To resolve this, lots of MIMO technology like single user MIMO (SU-MIMO), multiuser MIMO (MU-MIMO) and network MIMO were used. However, these new MIMO also did not still fulfill the demand of end users. Massive MIMO is an advancement of MIMO technology used in the 5G network in which hundreds and thousands of antennas are attached with base stations to increase throughput and spectral efficiency. Multiple transmit and receive antennas are used in massive MIMO to increase the transmission rate and spectral efficiency. When multiple UEs generate downlink traffic simultaneously, massive MIMO gains higher capacity. Massive MIMO uses extra antennas to move energy into smaller regions of space to increase spectral efficiency and throughput [ 43 ]. In traditional systems data collection from smart sensors is a complex task as it increases latency, reduced data rate and reduced reliability. While massive MIMO with beamforming and huge multiplexing techniques can sense data from different sensors with low latency, high data rate and higher reliability. Massive MIMO will help in transmitting the data in real-time collected from different sensors to central monitoring locations for smart sensor applications like self-driving cars, healthcare centers, smart grids, smart cities, smart highways, smart homes, and smart enterprises [ 44 ].

Highlights of 5G Massive MIMO technology are as follows:

• Data rate: Massive MIMO is advised as the one of the dominant technologies to provide wireless high speed and high data rate in the gigabits per seconds.
• The relationship between wave frequency and antenna size: Both are inversely proportional to each other. It means lower frequency signals need a bigger antenna and vise versa.

Pictorial representation of multi-input and multi-output (MIMO).

• MIMO role in 5G: Massive MIMO will play a crucial role in the deployment of future 5G mobile communication as greater spectral and energy efficiency could be enabled.

State-of-the-Art Approaches

Plenty of approaches were proposed to resolve the issues of conventional MIMO [ 7 ].

The MIMO multirate, feed-forward controller is suggested by Mae et al. [ 46 ]. In the simulation, the proposed model generates the smooth control input, unlike the conventional MIMO, which generates oscillated control inputs. It also outperformed concerning the error rate. However, a combination of multirate and single rate can be used for better results.

The performance of stand-alone MIMO, distributed MIMO with and without corporation MIMO, was investigated by Panzner et al. [ 47 ]. In addition, an idea about the integration of large scale in the 5G technology was also presented. In the experimental analysis, different MIMO configurations are considered. The variation in the ratio of overall transmit antennas to spatial is deemed step-wise from equality to ten.

The simulation of massive MIMO noncooperative and cooperative systems for down-link behavior was performed by He et al. [ 48 ]. It depends on present LTE systems, which deal with various antennas in the base station set-up. It was observed that collaboration in different BS improves the system behaviors, whereas throughput is reduced slightly in this approach. However, a new method can be developed which can enhance both system behavior and throughput.

In [ 8 ], different approaches that increased the energy efficiency benefits provided by massive MIMO were presented. They analyzed the massive MIMO technology and described the detailed design of the energy consumption model for massive MIMO systems. This article has explored several techniques to enhance massive MIMO systems’ energy efficiency (EE) gains. This paper reviews standard EE-maximization approaches for the conventional massive MIMO systems, namely, scaling number of antennas, real-time implementing low-complexity operations at the base station (BS), power amplifier losses minimization, and radio frequency (RF) chain minimization requirements. In addition, open research direction is also identified.

In [ 49 ], various existing approaches based on different antenna selection and scheduling, user selection and scheduling, and joint antenna and user scheduling methods adopted in massive MIMO systems are presented in this paper. The objective of this survey article was to make awareness about the current research and future research direction in MIMO for systems. They analyzed that complete utilization of resources and bandwidth was the most crucial factor which enhances the sum rate.

In [ 50 ], authors discussed the development of various techniques for pilot contamination. To calculate the impact of pilot contamination in time division duplex (TDD) massive MIMO system, TDD and frequency division duplexing FDD patterns in massive MIMO techniques are used. They discussed different issues in pilot contamination in TDD massive MIMO systems with all the possible future directions of research. They also classified various techniques to generate the channel information for both pilot-based and subspace-based approaches.

In [ 19 ], the authors defined the uplink and downlink services for a massive MIMO system. In addition, it maintains a performance matrix that measures the impact of pilot contamination on different performances. They also examined the various application of massive MIMO such as small cells, orthogonal frequency-division multiplexing (OFDM) schemes, massive MIMO IEEE 802, 3rd generation partnership project (3GPP) specifications, and higher frequency bands. They considered their research work crucial for cutting edge massive MIMO and covered many issues like system throughput performance and channel state acquisition at higher frequencies.

In [ 13 ], various approaches were suggested for MIMO future generation wireless communication. They made a comparative study based on performance indicators such as peak data rate, energy efficiency, latency, throughput, etc. The key findings of this survey are as follows: (1) spatial multiplexing improves the energy efficiency; (2) design of MIMO play a vital role in the enhancement of throughput; (3) enhancement of mMIMO focusing on energy & spectral performance; (4) discussed the future challenges to improve the system design.

In [ 51 ], the study of large-scale MIMO systems for an energy-efficient system sharing method was presented. For the resource allocation, circuit energy and transmit energy expenditures were taken into consideration. In addition, the optimization techniques were applied for an energy-efficient resource sharing system to enlarge the energy efficiency for individual QoS and energy constraints. The author also examined the BS configuration, which includes homogeneous and heterogeneous UEs. While simulating, they discussed that the total number of transmit antennas plays a vital role in boosting energy efficiency. They highlighted that the highest energy efficiency was obtained when the BS was set up with 100 antennas that serve 20 UEs.

This section includes various works done on 5G MIMO technology by different author’s. Table 5 shows how different author’s worked on improvement of various parameters such as throughput, latency, energy efficiency, and spectral efficiency with 5G MIMO technology.

Summary of massive MIMO-based approaches in 5G technology.

4.2. 5G Non-Orthogonal Multiple Access (NOMA)

NOMA is a very important radio access technology used in next generation wireless communication. Compared to previous orthogonal multiple access techniques, NOMA offers lots of benefits like high spectrum efficiency, low latency with high reliability and high speed massive connectivity. NOMA mainly works on a baseline to serve multiple users with the same resources in terms of time, space and frequency. NOMA is mainly divided into two main categories one is code domain NOMA and another is power domain NOMA. Code-domain NOMA can improve the spectral efficiency of mMIMO, which improves the connectivity in 5G wireless communication. Code-domain NOMA was divided into some more multiple access techniques like sparse code multiple access, lattice-partition multiple access, multi-user shared access and pattern-division multiple access [ 52 ]. Power-domain NOMA is widely used in 5G wireless networks as it performs well with various wireless communication techniques such as MIMO, beamforming, space-time coding, network coding, full-duplex and cooperative communication etc. [ 53 ]. The conventional orthogonal frequency-division multiple access (OFDMA) used by 3GPP in 4G LTE network provides very low spectral efficiency when bandwidth resources are allocated to users with low channel state information (CSI). NOMA resolved this issue as it enables users to access all the subcarrier channels so bandwidth resources allocated to the users with low CSI can still be accessed by the users with strong CSI which increases the spectral efficiency. The 5G network will support heterogeneous architecture in which small cell and macro base stations work for spectrum sharing. NOMA is a key technology of the 5G wireless system which is very helpful for heterogeneous networks as multiple users can share their data in a small cell using the NOMA principle.The NOMA is helpful in various applications like ultra-dense networks (UDN), machine to machine (M2M) communication and massive machine type communication (mMTC). As NOMA provides lots of features it has some challenges too such as NOMA needs huge computational power for a large number of users at high data rates to run the SIC algorithms. Second, when users are moving from the networks, to manage power allocation optimization is a challenging task for NOMA [ 54 ]. Hybrid NOMA (HNOMA) is a combination of power-domain and code-domain NOMA. HNOMA uses both power differences and orthogonal resources for transmission among multiple users. As HNOMA is using both power-domain NOMA and code-domain NOMA it can achieve higher spectral efficiency than Power-domain NOMA and code-domain NOMA. In HNOMA multiple groups can simultaneously transmit signals at the same time. It uses a message passing algorithm (MPA) and successive interference cancellation (SIC)-based detection at the base station for these groups [ 55 ].

Highlights of 5G NOMA technology as follows:

Pictorial representation of orthogonal and Non-Orthogonal Multiple Access (NOMA).

• NOMA provides higher data rates and resolves all the loop holes of OMA that makes 5G mobile network more scalable and reliable.
• As multiple users use same frequency band simultaneously it increases the performance of whole network.
• To setup intracell and intercell interference NOMA provides nonorthogonal transmission on the transmitter end.
• The primary fundamental of NOMA is to improve the spectrum efficiency by strengthening the ramification of receiver.

State-of-the-Art of Approaches

A plenty of approaches were developed to address the various issues in NOMA.

A novel approach to address the multiple receiving signals at the same frequency is proposed in [ 22 ]. In NOMA, multiple users use the same sub-carrier, which improves the fairness and throughput of the system. As a nonorthogonal method is used among multiple users, at the time of retrieving the user’s signal at the receiver’s end, joint processing is required. They proposed solutions to optimize the receiver and the radio resource allocation of uplink NOMA. Firstly, the authors proposed an iterative MUDD which utilizes the information produced by the channel decoder to improve the performance of the multiuser detector. After that, the author suggested a power allocation and novel subcarrier that enhances the users’ weighted sum rate for the NOMA scheme. Their proposed model showed that NOMA performed well as compared to OFDM in terms of fairness and efficiency.

In [ 53 ], the author’s reviewed a power-domain NOMA that uses superposition coding (SC) and successive interference cancellation (SIC) at the transmitter and the receiver end. Lots of analyses were held that described that NOMA effectively satisfies user data rate demands and network-level of 5G technologies. The paper presented a complete review of recent advances in the 5G NOMA system. It showed the comparative analysis regarding allocation procedures, user fairness, state-of-the-art efficiency evaluation, user pairing pattern, etc. The study also analyzes NOMA’s behavior when working with other wireless communication techniques, namely, beamforming, MIMO, cooperative connections, network, space-time coding, etc.

In [ 9 ], the authors proposed NOMA with MEC, which improves the QoS as well as reduces the latency of the 5G wireless network. This model increases the uplink NOMA by decreasing the user’s uplink energy consumption. They formulated an optimized NOMA framework that reduces the energy consumption of MEC by using computing and communication resource allocation, user clustering, and transmit powers.

In [ 10 ], the authors proposed a model which investigates outage probability under average channel state information CSI and data rate in full CSI to resolve the problem of optimal power allocation, which increase the NOMA downlink system among users. They developed simple low-complexity algorithms to provide the optimal solution. The obtained simulation results showed NOMA’s efficiency, achieving higher performance fairness compared to the TDMA configurations. It was observed from the results that NOMA, through the appropriate power amplifiers (PA), ensures the high-performance fairness requirement for the future 5G wireless communication networks.

In [ 56 ], researchers discussed that the NOMA technology and waveform modulation techniques had been used in the 5G mobile network. Therefore, this research gave a detailed survey of non-orthogonal waveform modulation techniques and NOMA schemes for next-generation mobile networks. By analyzing and comparing multiple access technologies, they considered the future evolution of these technologies for 5G mobile communication.

In [ 57 ], the authors surveyed non-orthogonal multiple access (NOMA) from the development phase to the recent developments. They have also compared NOMA techniques with traditional OMA techniques concerning information theory. The author discussed the NOMA schemes categorically as power and code domain, including the design principles, operating principles, and features. Comparison is based upon the system’s performance, spectral efficiency, and the receiver’s complexity. Also discussed are the future challenges, open issues, and their expectations of NOMA and how it will support the key requirements of 5G mobile communication systems with massive connectivity and low latency.

In [ 17 ], authors present the first review of an elementary NOMA model with two users, which clarify its central precepts. After that, a general design with multicarrier supports with a random number of users on each sub-carrier is analyzed. In performance evaluation with the existing approaches, resource sharing and multiple-input multiple-output NOMA are examined. Furthermore, they took the key elements of NOMA and its potential research demands. Finally, they reviewed the two-user SC-NOMA design and a multi-user MC-NOMA design to highlight NOMA’s basic approaches and conventions. They also present the research study about the performance examination, resource assignment, and MIMO in NOMA.

In this section, various works by different authors done on 5G NOMA technology is covered. Table 6 shows how other authors worked on the improvement of various parameters such as spectral efficiency, fairness, and computing capacity with 5G NOMA technology.

Summary of NOMA-based approaches in 5G technology.

4.3. 5G Millimeter Wave (mmWave)

Millimeter wave is an extremely high frequency band, which is very useful for 5G wireless networks. MmWave uses 30 GHz to 300 GHz spectrum band for transmission. The frequency band between 30 GHz to 300 GHz is known as mmWave because these waves have wavelengths between 1 to 10 mm. Till now radar systems and satellites are only using mmWave as these are very fast frequency bands which provide very high speed wireless communication. Many mobile network providers also started mmWave for transmitting data between base stations. Using two ways the speed of data transmission can be improved one is by increasing spectrum utilization and second is by increasing spectrum bandwidth. Out of these two approaches increasing bandwidth is quite easy and better. The frequency band below 5 GHz is very crowded as many technologies are using it so to boost up the data transmission rate 5G wireless network uses mmWave technology which instead of increasing spectrum utilization, increases the spectrum bandwidth [ 58 ]. To maximize the signal bandwidth in wireless communication the carrier frequency should also be increased by 5% because the signal bandwidth is directly proportional to carrier frequencies. The frequency band between 28 GHz to 60 GHz is very useful for 5G wireless communication as 28 GHz frequency band offers up to 1 GHz spectrum bandwidth and 60 GHz frequency band offers 2 GHz spectrum bandwidth. 4G LTE provides 2 GHz carrier frequency which offers only 100 MHz spectrum bandwidth. However, the use of mmWave increases the spectrum bandwidth 10 times, which leads to better transmission speeds [ 59 , 60 ].

Highlights of 5G mmWave are as follows:

Pictorial representation of millimeter wave.

• The 5G mmWave offer three advantages: (1) MmWave is very less used new Band, (2) MmWave signals carry more data than lower frequency wave, and (3) MmWave can be incorporated with MIMO antenna with the potential to offer a higher magnitude capacity compared to current communication systems.

In [ 11 ], the authors presented the survey of mmWave communications for 5G. The advantage of mmWave communications is adaptability, i.e., it supports the architectures and protocols up-gradation, which consists of integrated circuits, systems, etc. The authors over-viewed the present solutions and examined them concerning effectiveness, performance, and complexity. They also discussed the open research issues of mmWave communications in 5G concerning the software-defined network (SDN) architecture, network state information, efficient regulation techniques, and the heterogeneous system.

In [ 61 ], the authors present the recent work done by investigators in 5G; they discussed the design issues and demands of mmWave 5G antennas for cellular handsets. After that, they designed a small size and low-profile 60 GHz array of antenna units that contain 3D planer mesh-grid antenna elements. For the future prospect, a framework is designed in which antenna components are used to operate cellular handsets on mmWave 5G smartphones. In addition, they cross-checked the mesh-grid array of antennas with the polarized beam for upcoming hardware challenges.

In [ 12 ], the authors considered the suitability of the mmWave band for 5G cellular systems. They suggested a resource allocation system for concurrent D2D communications in mmWave 5G cellular systems, and it improves network efficiency and maintains network connectivity. This research article can serve as guidance for simulating D2D communications in mmWave 5G cellular systems. Massive mmWave BS may be set up to obtain a high delivery rate and aggregate efficiency. Therefore, many wireless users can hand off frequently between the mmWave base terminals, and it emerges the demand to search the neighbor having better network connectivity.

In [ 62 ], the authors provided a brief description of the cellular spectrum which ranges from 1 GHz to 3 GHz and is very crowed. In addition, they presented various noteworthy factors to set up mmWave communications in 5G, namely, channel characteristics regarding mmWave signal attenuation due to free space propagation, atmospheric gaseous, and rain. In addition, hybrid beamforming architecture in the mmWave technique is analyzed. They also suggested methods for the blockage effect in mmWave communications due to penetration damage. Finally, the authors have studied designing the mmWave transmission with small beams in nonorthogonal device-to-device communication.

This section covered various works done on 5G mmWave technology. The Table 7 shows how different author’s worked on the improvement of various parameters i.e., transmission rate, coverage, and cost, with 5G mmWave technology.

Summary of existing mmWave-based approaches in 5G technology.

4.4. 5G IoT Based Approaches

The 5G mobile network plays a big role in developing the Internet of Things (IoT). IoT will connect lots of things with the internet like appliances, sensors, devices, objects, and applications. These applications will collect lots of data from different devices and sensors. 5G will provide very high speed internet connectivity for data collection, transmission, control, and processing. 5G is a flexible network with unused spectrum availability and it offers very low cost deployment that is why it is the most efficient technology for IoT [ 63 ]. In many areas, 5G provides benefits to IoT, and below are some examples:

Smart homes: smart home appliances and products are in demand these days. The 5G network makes smart homes more real as it offers high speed connectivity and monitoring of smart appliances. Smart home appliances are easily accessed and configured from remote locations using the 5G network, as it offers very high speed low latency communication.

Smart cities: 5G wireless network also helps in developing smart cities applications such as automatic traffic management, weather update, local area broadcasting, energy saving, efficient power supply, smart lighting system, water resource management, crowd management, emergency control, etc.

Industrial IoT: 5G wireless technology will provide lots of features for future industries such as safety, process tracking, smart packing, shipping, energy efficiency, automation of equipment, predictive maintenance and logistics. 5G smart sensor technology also offers smarter, safer, cost effective, and energy-saving industrial operation for industrial IoT.

Smart Farming: 5G technology will play a crucial role for agriculture and smart farming. 5G sensors and GPS technology will help farmers to track live attacks on crops and manage them quickly. These smart sensors can also be used for irrigation control, pest control, insect control, and electricity control.

Autonomous Driving: 5G wireless network offers very low latency high speed communication which is very significant for autonomous driving. It means self-driving cars will come to real life soon with 5G wireless networks. Using 5G autonomous cars can easily communicate with smart traffic signs, objects and other vehicles running on the road. 5G’s low latency feature makes self-driving more real as every millisecond is important for autonomous vehicles, decision taking is performed in microseconds to avoid accidents [ 64 ].

Highlights of 5G IoT are as follows:

Pictorial representation of IoT with 5G.

• 5G with IoT is a new feature of next-generation mobile communication, which provides a high-speed internet connection between moderated devices. 5G IoT also offers smart homes, smart devices, sensors, smart transportation systems, smart industries, etc., for end-users to make them smarter.
• IoT deals with moderate devices which connect through the internet. The approach of the IoT has made the consideration of the research associated with the outcome of providing wearable, smart-phones, sensors, smart transportation systems, smart devices, washing machines, tablets, etc., and these diverse systems are associated to a common interface with the intelligence to connect.
• Significant IoT applications include private healthcare systems, traffic management, industrial management, and tactile internet, etc.

Plenty of approaches is devised to address the issues of IoT [ 14 , 65 , 66 ].

In [ 65 ], the paper focuses on 5G mobile systems due to the emerging trends and developing technologies, which results in the exponential traffic growth in IoT. The author surveyed the challenges and demands during deployment of the massive IoT applications with the main focus on mobile networking. The author reviewed the features of standard IoT infrastructure, along with the cellular-based, low-power wide-area technologies (LPWA) such as eMTC, extended coverage (EC)-GSM-IoT, as well as noncellular, low-power wide-area (LPWA) technologies such as SigFox, LoRa etc.

In [ 14 ], the authors presented how 5G technology copes with the various issues of IoT today. It provides a brief review of existing and forming 5G architectures. The survey indicates the role of 5G in the foundation of the IoT ecosystem. IoT and 5G can easily combine with improved wireless technologies to set up the same ecosystem that can fulfill the current requirement for IoT devices. 5G can alter nature and will help to expand the development of IoT devices. As the process of 5G unfolds, global associations will find essentials for setting up a cross-industry engagement in determining and enlarging the 5G system.

In [ 66 ], the author introduced an IoT authentication scheme in a 5G network, with more excellent reliability and dynamic. The scheme proposed a privacy-protected procedure for selecting slices; it provided an additional fog node for proper data transmission and service types of the subscribers, along with service-oriented authentication and key understanding to maintain the secrecy, precision of users, and confidentiality of service factors. Users anonymously identify the IoT servers and develop a vital channel for service accessibility and data cached on local fog nodes and remote IoT servers. The author performed a simulation to manifest the security and privacy preservation of the user over the network.

This section covered various works done on 5G IoT by multiple authors. Table 8 shows how different author’s worked on the improvement of numerous parameters, i.e., data rate, security requirement, and performance with 5G IoT.

Summary of IoT-based approaches in 5G technology.

4.5. Machine Learning Techniques for 5G

Various machine learning (ML) techniques were applied in 5G networks and mobile communication. It provides a solution to multiple complex problems, which requires a lot of hand-tuning. ML techniques can be broadly classified as supervised, unsupervised, and reinforcement learning. Let’s discuss each learning technique separately and where it impacts the 5G network.

Supervised Learning, where user works with labeled data; some 5G network problems can be further categorized as classification and regression problems. Some regression problems such as scheduling nodes in 5G and energy availability can be predicted using Linear Regression (LR) algorithm. To accurately predict the bandwidth and frequency allocation Statistical Logistic Regression (SLR) is applied. Some supervised classifiers are applied to predict the network demand and allocate network resources based on the connectivity performance; it signifies the topology setup and bit rates. Support Vector Machine (SVM) and NN-based approximation algorithms are used for channel learning based on observable channel state information. Deep Neural Network (DNN) is also employed to extract solutions for predicting beamforming vectors at the BS’s by taking mapping functions and uplink pilot signals into considerations.

In unsupervised Learning, where the user works with unlabeled data, various clustering techniques are applied to enhance network performance and connectivity without interruptions. K-means clustering reduces the data travel by storing data centers content into clusters. It optimizes the handover estimation based on mobility pattern and selection of relay nodes in the V2V network. Hierarchical clustering reduces network failure by detecting the intrusion in the mobile wireless network; unsupervised soft clustering helps in reducing latency by clustering fog nodes. The nonparametric Bayesian unsupervised learning technique reduces traffic in the network by actively serving the user’s requests and demands. Other unsupervised learning techniques such as Adversarial Auto Encoders (AAE) and Affinity Propagation Clustering techniques detect irregular behavior in the wireless spectrum and manage resources for ultradense small cells, respectively.

In case of an uncertain environment in the 5G wireless network, reinforcement learning (RL) techniques are employed to solve some problems. Actor-critic reinforcement learning is used for user scheduling and resource allocation in the network. Markov decision process (MDP) and Partially Observable MDP (POMDP) is used for Quality of Experience (QoE)-based handover decision-making for Hetnets. Controls packet call admission in HetNets and channel access process for secondary users in a Cognitive Radio Network (CRN). Deep RL is applied to decide the communication channel and mobility and speeds up the secondary user’s learning rate using an antijamming strategy. Deep RL is employed in various 5G network application parameters such as resource allocation and security [ 67 ]. Table 9 shows the state-of-the-art ML-based solution for 5G network.

The state-of-the-art ML-based solution for 5G network.

Highlights of machine learning techniques for 5G are as follows:

Pictorial representation of machine learning (ML) in 5G.

• In ML, a model will be defined which fulfills the desired requirements through which desired results are obtained. In the later stage, it examines accuracy from obtained results.
• ML plays a vital role in 5G network analysis for threat detection, network load prediction, final arrangement, and network formation. Searching for a better balance between power, length of antennas, area, and network thickness crossed with the spontaneous use of services in the universe of individual users and types of devices.

In [ 79 ], author’s firstly describes the demands for the traditional authentication procedures and benefits of intelligent authentication. The intelligent authentication method was established to improve security practice in 5G-and-beyond wireless communication systems. Thereafter, the machine learning paradigms for intelligent authentication were organized into parametric and non-parametric research methods, as well as supervised, unsupervised, and reinforcement learning approaches. As a outcome, machine learning techniques provide a new paradigm into authentication under diverse network conditions and unstable dynamics. In addition, prompt intelligence to the security management to obtain cost-effective, better reliable, model-free, continuous, and situation-aware authentication.

In [ 68 ], the authors proposed a machine learning-based model to predict the traffic load at a particular location. They used a mobile network traffic dataset to train a model that can calculate the total number of user requests at a time. To launch access and mobility management function (AMF) instances according to the requirement as there were no predictions of user request the performance automatically degrade as AMF does not handle these requests at a time. Earlier threshold-based techniques were used to predict the traffic load, but that approach took too much time; therefore, the authors proposed RNN algorithm-based ML to predict the traffic load, which gives efficient results.

In [ 15 ], authors discussed the issue of network slice admission, resource allocation among subscribers, and how to maximize the profit of infrastructure providers. The author proposed a network slice admission control algorithm based on SMDP (decision-making process) that guarantees the subscribers’ best acceptance policies and satisfiability (tenants). They also suggested novel N3AC, a neural network-based algorithm that optimizes performance under various configurations, significantly outperforms practical and straightforward approaches.

This section includes various works done on 5G ML by different authors. Table 10 shows the state-of-the-art work on the improvement of various parameters such as energy efficiency, Quality of Services (QoS), and latency with 5G ML.

The state-of-the-art ML-based approaches in 5G technology.

4.6. Optimization Techniques for 5G

Optimization techniques may be applied to capture NP-Complete or NP-Hard problems in 5G technology. This section briefly describes various research works suggested for 5G technology based on optimization techniques.

In [ 80 ], Massive MIMO technology is used in 5G mobile network to make it more flexible and scalable. The MIMO implementation in 5G needs a significant number of radio frequencies is required in the RF circuit that increases the cost and energy consumption of the 5G network. This paper provides a solution that increases the cost efficiency and energy efficiency with many radio frequency chains for a 5G wireless communication network. They give an optimized energy efficient technique for MIMO antenna and mmWave technologies based 5G mobile communication network. The proposed Energy Efficient Hybrid Precoding (EEHP) algorithm to increase the energy efficiency for the 5G wireless network. This algorithm minimizes the cost of an RF circuit with a large number of RF chains.

In [ 16 ], authors have discussed the growing demand for energy efficiency in the next-generation networks. In the last decade, they have figured out the things in wireless transmissions, which proved a change towards pursuing green communication for the next generation system. The importance of adopting the correct EE metric was also reviewed. Further, they worked through the different approaches that can be applied in the future for increasing the network’s energy and posed a summary of the work that was completed previously to enhance the energy productivity of the network using these capabilities. A system design for EE development using relay selection was also characterized, along with an observation of distinct algorithms applied for EE in relay-based ecosystems.

In [ 81 ], authors presented how AI-based approach is used to the setup of Self Organizing Network (SON) functionalities for radio access network (RAN) design and optimization. They used a machine learning approach to predict the results for 5G SON functionalities. Firstly, the input was taken from various sources; then, prediction and clustering-based machine learning models were applied to produce the results. Multiple AI-based devices were used to extract the knowledge analysis to execute SON functionalities smoothly. Based on results, they tested how self-optimization, self-testing, and self-designing are done for SON. The author also describes how the proposed mechanism classifies in different orders.

In [ 82 ], investigators examined the working of OFDM in various channel environments. They also figured out the changes in frame duration of the 5G TDD frame design. Subcarrier spacing is beneficial to obtain a small frame length with control overhead. They provided various techniques to reduce the growing guard period (GP) and cyclic prefix (CP) like complete utilization of multiple subcarrier spacing, management and data parts of frame at receiver end, various uses of timing advance (TA) or total control of flexible CP size.

This section includes various works that were done on 5G optimization by different authors. Table 11 shows how other authors worked on the improvement of multiple parameters such as energy efficiency, power optimization, and latency with 5G optimization.

Summary of Optimization Based Approaches in 5G Technology.

5. Description of Novel 5G Features over 4G

This section presents descriptions of various novel features of 5G, namely, the concept of small cell, beamforming, and MEC.

5.1. Small Cell

Small cells are low-powered cellular radio access nodes which work in the range of 10 meters to a few kilometers. Small cells play a very important role in implementation of the 5G wireless network. Small cells are low power base stations which cover small areas. Small cells are quite similar with all the previous cells used in various wireless networks. However, these cells have some advantages like they can work with low power and they are also capable of working with high data rates. Small cells help in rollout of 5G network with ultra high speed and low latency communication. Small cells in the 5G network use some new technologies like MIMO, beamforming, and mmWave for high speed data transmission. The design of small cells hardware is very simple so its implementation is quite easier and faster. There are three types of small cell tower available in the market. Femtocells, picocells, and microcells [ 83 ]. As shown in the Table 12 .

Types of Small cells.

MmWave is a very high band spectrum between 30 to 300 GHz. As it is a significantly less used spectrum, it provides very high-speed wireless communication. MmWave offers ultra-wide bandwidth for next-generation mobile networks. MmWave has lots of advantages, but it has some disadvantages, too, such as mmWave signals are very high-frequency signals, so they have more collision with obstacles in the air which cause the signals loses energy quickly. Buildings and trees also block MmWave signals, so these signals cover a shorter distance. To resolve these issues, multiple small cell stations are installed to cover the gap between end-user and base station [ 18 ]. Small cell covers a very shorter range, so the installation of a small cell depends on the population of a particular area. Generally, in a populated place, the distance between each small cell varies from 10 to 90 meters. In the survey [ 20 ], various authors implemented small cells with massive MIMO simultaneously. They also reviewed multiple technologies used in 5G like beamforming, small cell, massive MIMO, NOMA, device to device (D2D) communication. Various problems like interference management, spectral efficiency, resource management, energy efficiency, and backhauling are discussed. The author also gave a detailed presentation of all the issues occurring while implementing small cells with various 5G technologies. As shown in the Figure 7 , mmWave has a higher range, so it can be easily blocked by the obstacles as shown in Figure 7 a. This is one of the key concerns of millimeter-wave signal transmission. To solve this issue, the small cell can be placed at a short distance to transmit the signals easily, as shown in Figure 7 b.

Pictorial representation of communication with and without small cells.

5.2. Beamforming

Beamforming is a key technology of wireless networks which transmits the signals in a directional manner. 5G beamforming making a strong wireless connection toward a receiving end. In conventional systems when small cells are not using beamforming, moving signals to particular areas is quite difficult. Beamforming counter this issue using beamforming small cells are able to transmit the signals in particular direction towards a device like mobile phone, laptops, autonomous vehicle and IoT devices. Beamforming is improving the efficiency and saves the energy of the 5G network. Beamforming is broadly divided into three categories: Digital beamforming, analog beamforming and hybrid beamforming. Digital beamforming: multiuser MIMO is equal to digital beamforming which is mainly used in LTE Advanced Pro and in 5G NR. In digital beamforming the same frequency or time resources can be used to transmit the data to multiple users at the same time which improves the cell capacity of wireless networks. Analog Beamforming: In mmWave frequency range 5G NR analog beamforming is a very important approach which improves the coverage. In digital beamforming there are chances of high pathloss in mmWave as only one beam per set of antenna is formed. While the analog beamforming saves high pathloss in mmWave. Hybrid beamforming: hybrid beamforming is a combination of both analog beamforming and digital beamforming. In the implementation of MmWave in 5G network hybrid beamforming will be used [ 84 ].

Wireless signals in the 4G network are spreading in large areas, and nature is not Omnidirectional. Thus, energy depletes rapidly, and users who are accessing these signals also face interference problems. The beamforming technique is used in the 5G network to resolve this issue. In beamforming signals are directional. They move like a laser beam from the base station to the user, so signals seem to be traveling in an invisible cable. Beamforming helps achieve a faster data rate; as the signals are directional, it leads to less energy consumption and less interference. In [ 21 ], investigators evolve some techniques which reduce interference and increase system efficiency of the 5G mobile network. In this survey article, the authors covered various challenges faced while designing an optimized beamforming algorithm. Mainly focused on different design parameters such as performance evaluation and power consumption. In addition, they also described various issues related to beamforming like CSI, computation complexity, and antenna correlation. They also covered various research to cover how beamforming helps implement MIMO in next-generation mobile networks [ 85 ]. Figure 8 shows the pictorial representation of communication with and without using beamforming.

Pictorial Representation of communication with and without using beamforming.

5.3. Mobile Edge Computing

Mobile Edge Computing (MEC) [ 24 ]: MEC is an extended version of cloud computing that brings cloud resources closer to the end-user. When we talk about computing, the very first thing that comes to our mind is cloud computing. Cloud computing is a very famous technology that offers many services to end-user. Still, cloud computing has many drawbacks. The services available in the cloud are too far from end-users that create latency, and cloud user needs to download the complete application before use, which also increases the burden to the device [ 86 ]. MEC creates an edge between the end-user and cloud server, bringing cloud computing closer to the end-user. Now, all the services, namely, video conferencing, virtual software, etc., are offered by this edge that improves cloud computing performance. Another essential feature of MEC is that the application is split into two parts, which, first one is available at cloud server, and the second is at the user’s device. Therefore, the user need not download the complete application on his device that increases the performance of the end user’s device. Furthermore, MEC provides cloud services at very low latency and less bandwidth. In [ 23 , 87 ], the author’s investigation proved that successful deployment of MEC in 5G network increases the overall performance of 5G architecture. Graphical differentiation between cloud computing and mobile edge computing is presented in Figure 9 .

Pictorial representation of cloud computing vs. mobile edge computing.

6. 5G Security

Security is the key feature in the telecommunication network industry, which is necessary at various layers, to handle 5G network security in applications such as IoT, Digital forensics, IDS and many more [ 88 , 89 ]. The authors [ 90 ], discussed the background of 5G and its security concerns, challenges and future directions. The author also introduced the blockchain technology that can be incorporated with the IoT to overcome the challenges in IoT. The paper aims to create a security framework which can be incorporated with the LTE advanced network, and effective in terms of cost, deployment and QoS. In [ 91 ], author surveyed various form of attacks, the security challenges, security solutions with respect to the affected technology such as SDN, Network function virtualization (NFV), Mobile Clouds and MEC, and security standardizations of 5G, i.e., 3GPP, 5GPPP, Internet Engineering Task Force (IETF), Next Generation Mobile Networks (NGMN), European Telecommunications Standards Institute (ETSI). In [ 92 ], author elaborated various technological aspects, security issues and their existing solutions and also mentioned the new emerging technological paradigms for 5G security such as blockchain, quantum cryptography, AI, SDN, CPS, MEC, D2D. The author aims to create new security frameworks for 5G for further use of this technology in development of smart cities, transportation and healthcare. In [ 93 ], author analyzed the threats and dark threat, security aspects concerned with SDN and NFV, also their Commercial & Industrial Security Corporation (CISCO) 5G vision and new security innovations with respect to the new evolving architectures of 5G [ 94 ].

AuthenticationThe identification of the user in any network is made with the help of authentication. The different mobile network generations from 1G to 5G have used multiple techniques for user authentication. 5G utilizes the 5G Authentication and Key Agreement (AKA) authentication method, which shares a cryptographic key between user equipment (UE) and its home network and establishes a mutual authentication process between the both [ 95 ].

Access Control To restrict the accessibility in the network, 5G supports access control mechanisms to provide a secure and safe environment to the users and is controlled by network providers. 5G uses simple public key infrastructure (PKI) certificates for authenticating access in the 5G network. PKI put forward a secure and dynamic environment for the 5G network. The simple PKI technique provides flexibility to the 5G network; it can scale up and scale down as per the user traffic in the network [ 96 , 97 ].

Communication Security 5G deals to provide high data bandwidth, low latency, and better signal coverage. Therefore secure communication is the key concern in the 5G network. UE, mobile operators, core network, and access networks are the main focal point for the attackers in 5G communication. Some of the common attacks in communication at various segments are Botnet, message insertion, micro-cell, distributed denial of service (DDoS), and transport layer security (TLS)/secure sockets layer (SSL) attacks [ 98 , 99 ].

Encryption The confidentiality of the user and the network is done using encryption techniques. As 5G offers multiple services, end-to-end (E2E) encryption is the most suitable technique applied over various segments in the 5G network. Encryption forbids unauthorized access to the network and maintains the data privacy of the user. To encrypt the radio traffic at Packet Data Convergence Protocol (PDCP) layer, three 128-bits keys are applied at the user plane, nonaccess stratum (NAS), and access stratum (AS) [ 100 ].

7. Summary of 5G Technology Based on Above-Stated Challenges

In this section, various issues addressed by investigators in 5G technologies are presented in Table 13 . In addition, different parameters are considered, such as throughput, latency, energy efficiency, data rate, spectral efficiency, fairness & computing capacity, transmission rate, coverage, cost, security requirement, performance, QoS, power optimization, etc., indexed from R1 to R14.

Summary of 5G Technology above stated challenges (R1:Throughput, R2:Latency, R3:Energy Efficiency, R4:Data Rate, R5:Spectral efficiency, R6:Fairness & Computing Capacity, R7:Transmission Rate, R8:Coverage, R9:Cost, R10:Security requirement, R11:Performance, R12:Quality of Services (QoS), R13:Power Optimization).

8. Conclusions

This survey article illustrates the emergence of 5G, its evolution from 1G to 5G mobile network, applications, different research groups, their work, and the key features of 5G. It is not just a mobile broadband network, different from all the previous mobile network generations; it offers services like IoT, V2X, and Industry 4.0. This paper covers a detailed survey from multiple authors on different technologies in 5G, such as massive MIMO, Non-Orthogonal Multiple Access (NOMA), millimeter wave, small cell, MEC (Mobile Edge Computing), beamforming, optimization, and machine learning in 5G. After each section, a tabular comparison covers all the state-of-the-research held in these technologies. This survey also shows the importance of these newly added technologies and building a flexible, scalable, and reliable 5G network.

9. Future Findings

This article covers a detailed survey on the 5G mobile network and its features. These features make 5G more reliable, scalable, efficient at affordable rates. As discussed in the above sections, numerous technical challenges originate while implementing those features or providing services over a 5G mobile network. So, for future research directions, the research community can overcome these challenges while implementing these technologies (MIMO, NOMA, small cell, mmWave, beam-forming, MEC) over a 5G network. 5G communication will bring new improvements over the existing systems. Still, the current solutions cannot fulfill the autonomous system and future intelligence engineering requirements after a decade. There is no matter of discussion that 5G will provide better QoS and new features than 4G. But there is always room for improvement as the considerable growth of centralized data and autonomous industry 5G wireless networks will not be capable of fulfilling their demands in the future. So, we need to move on new wireless network technology that is named 6G. 6G wireless network will bring new heights in mobile generations, as it includes (i) massive human-to-machine communication, (ii) ubiquitous connectivity between the local device and cloud server, (iii) creation of data fusion technology for various mixed reality experiences and multiverps maps. (iv) Focus on sensing and actuation to control the network of the entire world. The 6G mobile network will offer new services with some other technologies; these services are 3D mapping, reality devices, smart homes, smart wearable, autonomous vehicles, artificial intelligence, and sense. It is expected that 6G will provide ultra-long-range communication with a very low latency of 1 ms. The per-user bit rate in a 6G wireless network will be approximately 1 Tbps, and it will also provide wireless communication, which is 1000 times faster than 5G networks.

Acknowledgments

Author contributions.

Conceptualization: R.D., I.Y., G.C., P.L. data gathering: R.D., G.C., P.L, I.Y. funding acquisition: I.Y. investigation: I.Y., G.C., G.P. methodology: R.D., I.Y., G.C., P.L., G.P., survey: I.Y., G.C., P.L, G.P., R.D. supervision: G.C., I.Y., G.P. validation: I.Y., G.P. visualization: R.D., I.Y., G.C., P.L. writing, original draft: R.D., I.Y., G.C., P.L., G.P. writing, review, and editing: I.Y., G.C., G.P. All authors have read and agreed to the published version of the manuscript.

This paper was supported by Soonchunhyang University.

Institutional Review Board Statement

Informed consent statement, data availability statement, conflicts of interest.

The authors declare no conflict of interest.

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• Published: 27 September 2024

Connectivity in crisis: the contrasting roles of mobile and non-mobile Internet on subjective well-being during the COVID-19 pandemic

• Xiongkai Tan 1 , 2 ,
• Sha Zhang   ORCID: orcid.org/0000-0002-1266-8919 1 , 3 ,
• Ruichen Ge 1 , 2 &
• Hong Zhao 1  

Humanities and Social Sciences Communications volume  11 , Article number:  1255 ( 2024 ) Cite this article

Metrics details

• Information systems and information technology
• Science, technology and society

As the COVID-19 pandemic has accelerated the shift towards mobile Internet while decreasing traditional, non-mobile Internet usage, understanding the implications of this trend on individuals’ subjective well-being has become particularly crucial. While the distinction in connectivity is evident, the specific ways in which each modality influences subjective well-being are not well documented. This study, grounded in the uses and gratifications theory, asserts that while both Internet types fulfil some similar gratifications, their unique gratifications lead to varying impacts on subjective well-being in normal and socially disruptive times. Utilising a representative longitudinal dataset from China comprising 46,803 observations from 15,601 individuals, our findings indicate that traditional Internet generally exerts a more positive influence on subjective well-being than mobile Internet. However, the role of mobile Internet has become significantly more pronounced during the COVID-19 pandemic. We further reveal the substitution effect between mobile and non-mobile Internet, which diminished during the COVID-19 pandemic. This study offers novel insights into the comparative effects of mobile and traditional Internet on subjective well-being, especially during social disturbances. This research contributes to a deeper understanding of technology’s role in enhancing subjective well-being, as well as in mitigating the impacts of crises.

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Introduction.

The past decades have witnessed the proliferation of the Internet and corresponding dramatic changes in individuals’ daily lives. As of January 2024, the number of Internet users worldwide had grown to 5.36 billion, with users spending an average of 6.67 h daily on the Internet (Data Reportal 2024 ). The Internet has emerged as a pivotal hub for an array of activities, including communication, information search, leisure pursuits, and social interactions (Katz and Koutroumpis 2013 ; Orben and Przybylski 2019 ; Tong et al. 2021 ). Especially during the COVID-19 pandemic, various control measures, such as lockdowns and social distancing, have prevented physical contact, making people even more dependent on the Internet (Chen et al. 2020 ; Feldmann et al. 2021 ). According to Genie Networks ( 2020 ), the traffic of major Asian network operators increased by approximately 49% after the COVID-19 outbreak.

The impact of Internet usage on subjective well-being has garnered significant attention from scholars (Castellacci and Tveito 2018 ; Lu and Kandilov 2021 ). Subjective well-being is a crucial part of mental health and overall quality of life (Diener 2000 ) contributing to reduced health risks and longevity (Diener and Chan 2011 ; Iwasa et al. 2006 ; Yu et al. 2016 ). Protecting subjective well-being is essential for maintaining overall health, particularly during challenging times (Pierce et al. 2020 ; Qiu et al. 2020 ). The existing research indicates that Internet usage can enhance subjective well-being; the Internet allows remote communication, thereby strengthening users’ social connections (Li and Zhou 2021 ). Additionally, it provides individuals with access to richer information (Lian and Yen 2014 ) and enables them to engage in a more diverse range of activities (Wong et al. 2014 ).

To date, the extant literature has largely focused on general Internet usage (e.g. Khalilaila and Vitman-Schorr 2018 ; Li and Zhou 2021 ), without considering the differences between various types of Internet services. Recently, there has been a rapid increase in the use of the mobile Internet (Lu and Kandilov 2021 ), which primarily refers to Internet access via handheld devices such as smartphones and tablets. In contrast, traditional non-mobile Internet is accessed through personal computers and laptops (de Haan et al. 2018 ; Napoli and Obar 2014 ). These two types of the Internet exhibit significant differences in terms of technical capabilities and usage patterns (Chae and Kim 2003 ; Pearce and Rice 2013 ). For example, the traditional non-mobile Internet tends to have higher levels of available resources and stronger multimedia processing capabilities, whereas the mobile Internet offers a higher degree of personalisation and convenience of access (Napoli and Obar 2014 ). These differences may lead to different gratifications and consequently have varying effects on subjective well-being. A few studies have explored the relevance of mobile Internet. Lu and Kandilov ( 2021 ) suggest that mobile Internet usage can enhance social relationships, thereby improving subjective well-being and extending general Internet findings to the mobile context. However, the distinct impacts of these two types of Internet on subjective well-being have not yet received sufficient attention.

To enhance the understanding of the differences between mobile and non-mobile Internet and strategies to promote subjective well-being, we aim to answer the following questions: (1) How does the impact of mobile Internet on subjective well-being compare to that of the traditional non-mobile Internet? (2) How does the impact of mobile and non-mobile Internet use on subjective well-being change during times of societal disruption such as the COVID-19 pandemic? (3) How do mobile and non-mobile Internet interact to affect subjective well-being?

The remainder of this paper is organised as follows. The second section introduces the theoretical background and develops the hypotheses. The third section describes the method and data used. The forth section describes the findings of the research, and the fifth section presents the conclusions and discusses the contributions and limitations of the study.

Theoretical background and hypotheses

Uses and gratifications theory.

We integrate the uses and gratifications theory (UGT) into our conceptual reasoning to explain why mobile and non-mobile Internet play different roles in enhancing subjective well-being and how their effects interact and evolve during times of societal disruption such as the COVID-19 pandemic. Scholars have proposed that the UGT can explain how individuals use specific media to meet their needs and achieve gratification (Blumler 1979 ; Katz et al. 1973 ) and can serve as a powerful tool for understanding the interaction between information technology and people. Scholars have applied the UGT to a wide range of topics, including mobile phone applications (Gao 2023 ), e-commerce (Kukar-Kinney et al. 2022 ), social media (Whiting and Williams 2013 ), and the Internet (LaRose et al. 2001 ; Cho et al. 2003 ).

The UGT provides a user-centred perspective to explore the differences between mobile and non-mobile Internet focusing on the gratification they offer to users. The UGT suggests that users primarily engage with information technology to achieve various forms of gratification (Blumler 1979 ; Katz et al. 1973 ). First, users have diverse gratification needs such as entertainment, social interaction, information, and so forth. Different information technologies can fulfil one or more of these needs. For example, as Gao ( 2023 ) suggests smart mobile learning platforms offer multiple forms of gratification, including technological, hedonic, and functional. Mobile Internet shares several common gratification types with the traditional non-mobile Internet, including content, process, and social gratification (Stafford et al. 2004 ). However, the existing literature also underlines the distinctions between mobile and traditional Internet, which may be attributed to the different types of gratification they provide (Ghose et al. 2013 ; Song and Sela, 2023 ). Second, the gratification types sought by users are dynamic; changing environments can influence both the nature of sought gratifications and their prioritisation. Research has shown that societal shifts, such as the COVID-19 pandemic, significantly impact the interaction between individuals and information technology (Wilson-Nash et al. 2023 ). Accordingly, we incorporate a dynamic perspective into the UGT framework to investigate how societal disruptions affect the roles of mobile and non-mobile Internet.

The impact of mobile and non-mobile internet on subjective well-being

Both mobile and non-mobile Internet enable individuals to experience the gratification provided by Internet connectivity. Internet provides a powerful way for individuals to obtain rich information and content and interact with others, thereby contributing to an increase in well-being (Castellacci and Tveito 2018 ; Contarello and Sarrica 2007 ; Graham and Nikolova 2013 ; Lu and Kandilov 2021 ). Stafford et al. ( 2004 ) suggest that Internet usage plays an important role in at least three categories of gratification. The first is content gratification, in which individuals benefit from the information and materials provided by the Internet. The second is process gratification, where users gain satisfaction through Internet surfing behaviour, including both random browsing and purposeful navigation. The last is social gratification, through which users can leverage the Internet to build and enhance their social connections.

Although both mobile and non-mobile Internet provide gratification types that may be associated with increased subjective well-being, their differences could lead to variances in effect sizes. First, non-mobile Internet offers higher levels of functionality and content availability than mobile Internet (Chae and Kim 2003 ; Napoli and Obar 2014 ), facilitating easier attainment of user gratification. Although it is criticised as inferior compared to traditional non-mobile device-based access, mobile Internet provides an affordable way for those without traditional non-mobile to access the Internet. Non-mobile Internet possesses stronger functionalities than mobile Internet and is associated with greater storage capacity, more powerful computing ability, faster speed, and more convenient interactive hardware. From a content perspective, mobile Internet faces greater limitations when dealing with high-intensity content, restricting activities that require high performance when using non-mobile Internet (Chae and Kim 2003 ). While mobile Internet technology has advanced rapidly, the performance disparity between fixed and mobile Internet remains significant. Fixed Internet has stronger computing power (Ludashi 2024 ) and faster network speeds (Data Reportal 2024 ) than mobile Internet. From the user’s standpoint, the user-friendly interactive hardware system of non-mobile Internet, including large keyboards and screens, offers a high level of ease of use and reduces users’ need to expend physical and mental efforts (Pearce and Rice 2013 ; Redlinger et al. 2021 ). Prior research underscores the impact of functionality on users. The smaller screen size of mobile Internet devices is related to lower usability, resulting in an increase in the cost of information consumption (Ghose et al. 2013 ) and making it more challenging for them to perform tasks that require a high cognitive load (Ilany-Tzur and Fink 2023 ). For instance, users process less fine-grained information when browsing mobile Internet (de Haan et al. 2018 ). Moreover, Melumad et al. ( 2019 ) observed that individuals tend to generate shorter content and limit the amount of information they share on their smartphones.

Second, the ubiquity of mobile Internet may increase the user burden and hinder gratification. Although the portability of mobile devices allows individuals to enjoy Internet access without limitations of place and time (Okazaki and Mendez 2013 ; Rapp et al. 2015 ), it also creates the burden of 24/7 connectivity (Vanden Abeele, Nguyen 2022 ). With the proliferation of mobile Internet, being permanently online and continuously connected has become increasingly expected and, in many cases, taken for granted (Vanden Abeele et al. 2018 ). Mobile Internet places individuals in a state of being ‘always-on’ (Nguyen 2021 ) or constantly ‘individually addressable’ 24/7 (Ling 2008 ; Mols and Pridmore 2021 ), a condition often experienced as a burden to well-being. Furthermore, the propensity for mobile Internet addiction raises academic concerns, with studies indicating that mobile devices can be more addictive than other technologies (Gutiérrez et al. 2016 ; Roberts et al. 2015 ; Zhan et al. 2021 ; Lin et al. 2016 ). Therefore, we anticipate that non-mobile Internet may have a stronger positive impact on subjective well-being than mobile Internet, leading to the following hypothesis:

H1: The positive impact of non-mobile Internet usage on subjective well-being is stronger than that of mobile Internet usage .

The impact of societal disruptions

The evolution of a social environment may shape individuals’ needs. Societal changes, such as the COVID-19 pandemic, can be a potent catalyst for changes in what types of gratification individuals seek. This global crisis disrupts the daily routines of individuals and undermine the subjective well-being of the public (Brooks et al. 2020 ; Wanberg et al. 2020 ). Individuals faced unprecedented levels of uncertainty, leading to a surge in levels of stress, anxiety, and depression (Petrović et al. 2022 ). This, in turn, heightens the demand for gratification related to emotional support and psychological soothing to mitigate psychological issues (Pfefferbaum and North, 2020 ). Wang et al. ( 2020 ) and Gao et al. ( 2020 ) find that the pandemic has intensified the public’s need for media content that provides reassurance, escapism, and the sense of connection, reflecting a shift towards gratification that addresses emotional and mental health issues. This evolving landscape underscores the dynamic nature of human gratification-seeking behaviour, especially in response to environmental stressors and societal upheavals. Research finds that, during the pandemic, individuals’ reliance on the Internet significantly increased, with more time spent online (Feldmann et al. 2021 ). Internet has become a crucial means of coping with psychological and mental issues caused by the pandemic. Luo et al. ( 2022 ) finds that a heightened perception of uncertainty is a key factor driving increased dependency on the Internet during COVID-19. In addition, the Internet has compensated for the lack of social support, with individuals experiencing lower levels of social support exhibiting greater dependency on the Internet during the pandemic (Li et al. 2021 ).

Compared to traditional non-mobile Internet, mobile Internet is associated with psychological pacifying gratification types and may play a significant role during periods of social disruption. Melumad and Pham ( 2021 ) points out that users are more inclined to use mobile Internet when feeling stressed, suggesting that mobile devices act as adult pacifiers and are a source of psychological comfort. On the one hand, mobile Internet is more personal and has a stronger connection with users’ identities. The high degree of personalisation in mobile Internet creates stronger physical (Melumad and Pham 2021 ), functional (Melumad and Meyer 2020 ), and emotional (Melumad et al. 2019 ) connections with users compared to traditional non-mobile Internet. The portability and unique ergonomic tactile sensation of smartphones allow mobile Internet to act as a transitional or attachment object, similar to the relationship between toddlers and their blankets or teddy bears (Melumad and Pham 2021 ; Passman 1977 ). This positioning of mobile Internet as a source of psychological comfort helps alleviate stress and protects subjective well-being during social disruptions.

On the other hand, mobile Internet is associated with the sense of control (Liu et al. 2019 ). Individuals with a lower sense of control may feel powerless about their decisions and ability to influence others. The use of mobile Internet creates a portable private personal territory for users (Hatuka and Toch 2016 ). This perceived sense of control can reduce the uncertainty that individuals experience (Ariely 2000 ) and becomes particularly salient during the chaos and uncertainty of societal disruptions (Wanberg et al. 2020 ). Previous research indicates that a sense of control is an important contributor to well-being (Lachman and Weaver 1998 ), with a higher level of perceived sense of control associated with greater subjective well-being (Anderson et al. 2012 ; Cheng et al. 2013 ). Hence, we propose the following:

H2: The relative impacts of mobile and non-mobile Internet usage on subjective well-being change in times of societal disruption; that is, the positive impact of mobile Internet usage on subjective well-being is enhanced during times of societal disruption .

The interaction between mobile and non-mobile internet

Individuals may use both mobile and non-mobile Internet simultaneously, and the interaction between these two types of Internet can impact subjective well-being. On the one hand, both forms share fundamental characteristics, providing users with network connectivity. Although traditional non-mobile Internet is associated with lower physical and mental effort (Pearce and Rice 2013 ; Redlinger et al. 2021 ), and mobile Internet is linked with portability and ubiquity in normal times (Okazaki and Mendez 2013 ; Rapp et al. 2015 ), they offer similar functionalities in fulfilling users’ gratifications sought from Internet use. Both satisfy users’ needs for content, process, and social gratification (Stafford et al. 2004 ). This high degree of overlap in roles might lead to a substitutional rather than a complementary relationship between mobile and non-mobile Internet usage. On the other hand, multichannel engagement is often associated with increased user stickiness (Liu et al. 2019 ; Shankar and Balasubramanian 2009 ; Verhoef et al. 2015 ). Users engaging with both types of Internet tend to have stronger online connections and spend more time online, which could displace time spent on other activities, reduce real-world social interactions, and increase dependence on online social media (Kraut et al. 1998 ; Orben and Przybylski, 2019 ; Tong et al. 2021 ). This, in turn, could lead to a range of psychological issues such as reduced self-esteem, and high levels of loneliness and stress (Donoso et al. 2021 ; Hanna et al. 2017 ; Odaci and Çikrikçi 2014 ; Özcan and Buzlu, 2007 ; Stead and Bibby 2017 ), thereby harming subjective well-being. Based on this, we posit the following:

H3: There exists a substitutional relationship between mobile and non-mobile Internet usage; specifically, the interaction between mobile and non-mobile Internet has a negative effect on subjective well-being .

During periods of social disruption, such as the COVID-19 pandemic, the interaction between mobile and non-mobile Internet may change. First, as mentioned earlier, besides fulfilling individual content, process, and social gratification similar to traditional Internet (Stafford et al. 2004 ), mobile Internet also provides a form of psychological pacifying gratification (Melumad and Pham 2021 ). During the pandemic, the demand for pacifying gratification from mobile Internet significantly increased, accentuating the differences between mobile and traditional Internet. The overlap in the roles of mobile and non-mobile Internet is reduced, thereby weakening their substitutive relationships.

Second, in normal times, the increased duration of Internet use due to multi-type Internet usage displaces time for real-world activities such as socialising and exercising (Kraut et al. 1998 ; Orben and Przybylski 2019 ; Tong et al. 2021 ). However, during the COVID-19 pandemic, lockdowns and social distancing measures prevented physical activity. This drastically altered users’ time usage patterns, creating significant amounts of free time that Internet usage could fill and helping users establish social connections and engage in leisure activities during periods of isolation (Nguyen et al. 2021 ). Social isolation results in increased stress, anxiety, and depression. People attempt to use the Internet to mitigate feelings of loneliness and psychological issues (Petrović et al. 2022 ), which weakens the negative impact of the interaction between mobile and non-mobile Internet. Therefore, we propose the following:

H4: During times of societal disruption, the substitution effect between mobile and non-mobile Internet usage on subjective well-being diminishes .

Methodology

Data and measurement.

We empirically examine these hypotheses by employing longitudinal data from a large, nationally representative sample of Chinese individuals. China is home to the largest Internet user community worldwide and had reached 1.011 billion Internet users as of June 2021 (China Internet Network Information Centre 2021 ). The expansion of the Internet user community provides a valuable opportunity to observe users’ adoption of different types of Internet and the consequences for well-being.

The China Family Panel Studies (CFPS) is a large longitudinal social survey launched by the Institute of Social Science Survey of Peking University. It is conducted every two years. Since 2016, the CFPS has distinguished between the different ways of accessing the Internet. Therefore, we constructed a balanced panel dataset based on three consecutive waves from 2016 onwards (i.e., 2016, 2018, and 2020). Data from the most recent wave (i.e., 2020) were collected between June and July 2020 after the outbreak of COVID-19, thus providing a valuable opportunity to investigate how societal disruptions shape the role of different types of Internet on individuals’ subjective well-being. We focused on observations without missing values for the key explanatory variables (mobile and non-mobile Internet usage) and response variables (subjective well-being). The final dataset includes 46,803 observations from 15,601 individuals.

The key explanatory variables of interest are mobile and traditional non-mobile Internet usage. Two binary variables are created as proxies for respondents’ Internet usage. \({{Mobile}}_{{it}}\) equals one if respondent \(i\) uses mobile devices, such as a mobile phone or tablet, to access the Internet (Lu and Kandilov 2021 ). \({{Non\_Mobile}}_{{it}}\) takes the value of one when respondent \(i\) uses traditional non-mobile devices, such as personal computers and laptop, to access the Internet.

\({{WellBeing}}_{{it}}\) is the key dependent variable. Depression is widely used to measure subjective well-being (Huppert and So 2013 ; Van Hemert et al. 2002 ; Wanberg et al. 2020 ). Subjective well-being is a comprehensive concept involving numerous dimensions, while mental health is widely recognised as an integral and fundamental component (Lachman and Weaver 1998 ). The CFPS uses the Centre for Epidemiologic Studies Depression Scale (CES-D) (Radloff 1977 ) to measure depressive symptoms (more details are provided in the Appendix ). For ease of interpretation, we apply an inverse transformation and standardised the score, with a score of 1 (0) indicating the highest (lowest) level of subjective well-being.

We also incorporate a set of control variables. First, we control for demographic characteristics. \({{Age}}_{{it}}\) is the age of respondent \(i\) at time \(t\) . \({{Female}}_{i}\) is a dummy variable that takes the value of one when respondent \(i\) is a female. \({{Edu}}_{{it}}\) is a dummy variable that indicates whether respondent \(i\) has received higher education. \({{Marriage}}_{{it}}\) is an indicator of the marital status of respondent \(i\) and takes the value of 1 when respondent \(i\) is married at time \(t\) . \({{Rural}}_{{it}}\) is equal to one when respondent \(i\) resides in a rural area at time \(t\) , otherwise zero. \({{Employ}}_{{it}}\) is a categorical variable covering four employment statuses: Employed, Unemployed, Exited the labour market, and Other. A five-point item of perceived relative income (What is your relative income level in your local area: 1 = very low to 5 = very high ) is adopted to measure \({{Income}}_{{it}}\) . We also incorporate province dummies to control for geographical differences. In addition, a dummy variable, \({{COVID}}_{t}\) , constructed as an indicator of the outbreak of COVID-19 and equals 1 after the outbreak of the pandemic.

Table 1 presents the descriptive statistics of the main variables and Table 2 shows the correlation matrix.

Analysis models

We use \({{WellBeing}}_{{it}}\) as the dependent variable in the empirical model. The key independent variables, \({{Mobile}}_{{it}}\) and \({{Non\_Mobile}}_{{it}}\) , are incorporated to capture the differential impacts of mobile and traditional non-mobile Internet usage. The baseline model is as follows:

where \(i\) denotes the respondent, \(t\) indicates time, and \(B\) represents the coefficient of the control variables. We perform panel regression, specifically using the random effect model, to estimate the coefficients. We first estimate the impact of mobile and non-mobile Internet usage on subjective well-being. We then add \({{COVID}}_{t}\) , along with its interactions with \({{Mobile}}_{{it}}\) and \({{Non\_Mobile}}_{{it}}\) into the baseline model to investigate how the pandemic shapes the impact of different Internet types. Following this, we incorporate the interaction between mobile and non-mobile Internet usage to explore any substitution effects on subjective well-being. Due to potential collinearity issues with high-order interaction terms, which may affect the estimation accuracy, we employ grouped regression to further explore the impact of the pandemic on the relationship between the two types of Internet usage.

Table 3 presents the estimated results, detailing the differential impacts of mobile and non-mobile Internet usage and their interaction. Table 4 illustrates how social disruptions shape their roles. The results indicate that both mobile and non-mobile Internet usage positively impacted subjective well-being, with the effect size of non-mobile Internet usage (b = 0.010, p  < 0.000) being larger than that of mobile Internet use (b = 0.003, p  = 0.048). Following the inversion and normalisation of scores from the CES-D depression scale, a recalculation reveals that, on average, mobile Internet usage reduced an individual’s CES-D depression scale score by 0.120, whereas non-mobile Internet usage resulted in a reduction of 0.541 points. Analysis of the confidence intervals further supports the relative magnitude of the impact of mobile versus non-mobile Internet usage. The effect size of mobile Internet usage (90% C.I. = [0.001, 0.006]) falls entirely to the left of the confidence interval or non-mobile Internet usage (90% C.I. = [0.007, 0.014]). After incorporating the interaction terms, the effect size for non-mobile Internet (b = 0.019, p  = 0.001) remains larger than that for mobile Internet (b = 0.003, p  = 0.090), thus supporting H1. Further analysis shows the interaction between \({{COVID}}_{t}\) and \({{Mobile}}_{{it}}\) is positive and significant (b = 0.011, p  = 0.000), suggesting that during the COVID-19 pandemic, the impact of mobile Internet usage on subjective well-being increase. The impact of non-mobile Internet usage does not change significantly during the societal disruption (b = −0.002, p  = 0.610). This finding supports H2.

Our results also shed light on how mobile and non-mobile Internet interact and how their relationship is influenced by societal disruptions. The coefficient of the interaction term between \({{Mobile}}_{{it}}\) and \({{Non\_Mobile}}_{{it}}\) is marginally significant and negative (b = −0.010, p  = 0.093), indicating that the relationship between mobile and non-mobile Internet on subjective well-being is substitutive rather than complementary. The concurrent use of both does not create a synergistic effect; instead, it diminishes the positive impact of Internet use on subjective well-being, which supports H3. A further subsample analysis reveals that, in the pre-COVID sample, the interaction term between the two types of Internet is also marginally significant and negative (b = −0.012, p  = 0.058), confirming the presence of a substitution effect. However, in the post-COVID sample, the interaction term becomes insignificant (b = −0.000, p  = 0.995), suggesting that societal disruptions weakened the substitution relationship between mobile and non-mobile Internet use on subjective well-being. Thus, H4 is supported, as shown in Fig. 1 .

The moderating role of societal disruption.

Based on a large-scale representative sample from China comprising 46,803 observations from 15,601 individuals across three periods before and after the outbreak of the COVID-19 pandemic, we scrutinise the effects of mobile and traditional non-mobile Internet on subjective well-being. Consistent with existing research on general Internet use (e.g. Li and Zhou 2021 ; Lian, Yen 2014 ) and a few studies on mobile Internet (e.g. Lu and Kandilov 2021 ), we find that both mobile and non-mobile Internet usage positively affect subjective well-being. However, these effects are not equivalent; traditional non-mobile Internet generally has a more substantial positive effect on well-being than mobile Internet. This may be attributed to the fact that mobile Internet serves as a more limited form of connectivity, with constraints on functionality and content access relative to its non-mobile counterpart (Chae and Kim 2003 ; Napoli and Obar 2014 ). In addition, we discover a substitution relationship between the two types of Internet usage. This suggests that by unpacking general Internet usage more closely, we might uncover more nuanced Internet-human interaction patterns, thereby enhancing our understanding of the Internet’s impact on human well-being.

Our study also demonstrates the unique role of mobile Internet in mitigating the impact of social disturbances on subjective well-being. Our data show that, unlike non-mobile Internet, mobile Internet significantly mitigated the COVID-19 outbreak’s negative impact on subjective well-being, indicating that mobile Internet provides a unique type of satisfaction that is not offered by other forms of Internet. Due to its highly personal nature, mobile Internet may act as a ‘pacifier’; that is, a source of psychological comfort during times of social disruption (Chae and Kim 2003 ; Liu et al. 2019 ; Melumad and Pham 2021 ). Although some may view mobile Internet as a downgraded version of non-mobile Internet, its lower cost leads to higher accessibility and a potentially greater social impact, suggesting the significant potential of mobile Internet technology in addressing social challenges.

Theoretical contributions

We contribute to the existing literature in three ways. First, it adds to the ongoing discussion on the role of information technology in enhancing well-being. The existing research primarily focuses on the impact of general Internet use on subjective well-being and does not differentiate between the impacts of various types of Internet (e.g. Khalilaila and Vitman-Schorr 2018 ; Paez et al. 2020 ; Li and Zhou 2021 ). While a few studies recognise the relevance of mobile Internet, they largely extend previous findings based on traditional, non-mobile Internet to the context of mobile Internet without deeply investigating the heterogeneity between mobile and traditional Internet. For example, Lu and Kandilov ( 2021 ) finds that mobile Internet can enhance social connections, thereby improving subjective well-being. Additionally, these studies often adopt a static perspective and pay less attention to the dynamic changes between Internet usage and subjective well-being. We undertake a novel comparative analysis of the different impacts of mobile and non-mobile Internet on subjective well-being, with a particular focus on the COVID-19 pandemic. Drawing on the UGT, we explore the unique gratifications that both mobile and non-mobile Internet provide. Overall, we find that while both Internet types can enhance subjective well-being, traditional Internet has a stronger effect. Social disturbances reverse this relationship, with mobile Internet playing a more significant role during times of social disruption. This deepens our understanding of the similarities and differences between mobile and non-mobile Internet and their impact on individuals’ welfare. Furthermore, we demonstrate the unique psychological comfort provided by mobile Internet, thus deepening our understanding of the societal implications of the widespread adoption of mobile Internet and the value of information technology in protecting subjective well-being in crisis situations.

Second, this study contributes to the literature on information technology and the COVID-19 pandemic. The extant literature primarily focuses on the increased use of the Internet resulting from the COVID-19 outbreak. The lockdowns and social distancing measures implemented in response to COVID-19 limited physical interactions, making Internet-based connections a significant part of individuals’ lives (Chen et al. 2020 ; Feldmann et al. 2021 ). Despite the fact that a substantial body of research finds that the pandemic leads individuals to spend more time online (e.g. Li et al. 2021 ; Luo et al. 2022 ), the psychological consequences of Internet use during the pandemic have received little attention. Our findings show a significant decline in subjective well-being due to the pandemic while also highlighting the compensating role of information technology. Mobile Internet can buffer the pandemic’s detrimental effects on subjective well-being. Our findings underscore the role of information technology during the pandemic and offer insights into how it can help individuals better withstand the impacts of societal disruptions.

Third, our work contributes to the expanding body of literature on UGT, which has been widely applied in information technology research, including studies on the Internet (LaRose et al. 2001 ; Cho et al. 2003 ), social media (Gan and Li 2018 ), e-commerce (Kukar-Kinney et al. 2022 ), and mobile applications (Gao 2023 ). While these studies highlight the evolution of media offerings, they often present a static perspective when examining the interactions between users and specific technologies or media platforms. The dynamic shifts in user preferences and priorities for different gratifications tend to be overlooked. Our research elucidates the dynamic nature of how the two types of Internet usage impact well-being, illustrating how grand societal disruptions influence the gratification that users seek. By shifting from static to dynamic views of user-technology interaction, we broaden the application scenarios of the UGT, thereby enhancing its explanatory power in understanding the complex dynamics between users and technology in rapidly evolving environments and contexts. Moreover, by introducing a novel category of gratification — the psychological soothing gratification provided by mobile Internet — we deepen our understanding of the Internet’s uses and gratifications, addressing Ruggiero’s ( 2000 ) call for theoretical updates to accommodate the evolution of media and the range of gratification types that new media can offer.

Limitations and future research

We close by the limitations of this research and suggesting avenues for future research. First, we measure Internet usage using two dummy variables; thus, we could not determine differences in the intensity of Internet use. Future research could use the hours or frequencies of different types of Internet usage to examine the effects of usage intensity on well-being. Second, we compared mobile and non-mobile Internet. However, with mobile Internet, the impact of tablet-based Internet access may differ from that of smartphone-based Internet access, similar to desktop- and laptop-based Internet access. Future research could consider these distinctions to explore the nuanced roles of different Internet types in fostering well-being. Third, we measure well-being by using the Centre for Epidemiologic Studies Depression Scale. Future research could use other proxies for well-being to determine whether the results hold for other components of subjective well-being. Finally, we analyse data from China, which is home to the largest online community. However, countries vary in their economies, cultures, and geography. Our findings demonstrate that the relationship between Internet use type and well-being is context-dependent. Hence, we encourage future research to extend this study using data from other countries to investigate the impact of geographical and cultural factors on the relationship between information technology and well-being.

Data availability

The datasets used for the analysis in this study can be accessed on the official website of the China Family Panel Studies at https://www.isss.pku.edu.cn/cfps/index.htm .

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Acknowledgements

This work was supported by the National Natural Science Foundation of China (NSFC: 72172146, 71972175, 71772169); the Fundamental Research Funds for the Central Universities (Grant Number Y95402AXX2).

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Tan, X., Zhang, S., Ge, R. et al. Connectivity in crisis: the contrasting roles of mobile and non-mobile Internet on subjective well-being during the COVID-19 pandemic. Humanit Soc Sci Commun 11 , 1255 (2024). https://doi.org/10.1057/s41599-024-03685-z

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DOI : https://doi.org/10.1057/s41599-024-03685-z

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• The Internet and the Pandemic

90% of Americans say the internet has been essential or important to them, many made video calls and 40% used technology in new ways. But while tech was a lifeline for some, others faced struggles

Table of contents.

• 1. How the internet and technology shaped Americans’ personal experiences amid COVID-19
• 2. Parents, their children and school during the pandemic
• 3. Navigating technological challenges
• 4. The role of technology in COVID-19 vaccine registration
• Acknowledgments
• Methodology

Pew Research Center has a long history of studying technology adoption trends and the impact of digital technology on society. This report focuses on American adults’ experiences with and attitudes about their internet and technology use during the COVID-19 outbreak. For this analysis, we surveyed 4,623 U.S. adults from April 12-18, 2021. Everyone who took part is a member of the Center’s American Trends Panel (ATP), an online survey panel that is recruited through national, random sampling of residential addresses. This way nearly all U.S. adults have a chance of selection. The survey is weighted to be representative of the U.S. adult population by gender, race, ethnicity, partisan affiliation, education and other categories. Read more about the  ATP’s methodology .

Chapter 1 of this report includes responses to an open-ended question and the overall report includes a number of quotations to help illustrate themes and add nuance to the survey findings. Quotations may have been lightly edited for grammar, spelling and clarity. The first three themes mentioned in each open-ended response, according to a researcher-developed codebook, were coded into categories for analysis. 

Here are the questions used for this report , along with responses, and its methodology .

The  coronavirus  has transformed many aspects of Americans’ lives. It  shut down  schools, businesses and workplaces and forced millions to  stay at home  for extended lengths of time. Public health authorities recommended  limits on social contact  to try to contain the spread of the virus, and these profoundly altered the way many worked, learned, connected with loved ones, carried out basic daily tasks, celebrated and mourned. For some, technology played a role in this transformation.  

Results from a new Pew Research Center survey of U.S. adults conducted April 12-18, 2021, reveal the extent to which people’s use of the internet has changed, their views about how helpful technology has been for them and the struggles some have faced. 

The vast majority of adults (90%) say the internet has been at least important to them personally during the pandemic, the survey finds. The share who say it has been  essential  – 58% – is up slightly from 53% in April 2020. There have also been upticks in the shares who say the internet has been essential in the past year among those with a bachelor’s degree or more formal education, adults under 30, and those 65 and older. 

A large majority of Americans (81%) also say they talked with others via video calls at some point since the pandemic’s onset. And for 40% of Americans, digital tools have taken on new relevance: They report they used technology or the internet in ways that were new or different to them. Some also sought upgrades to their service as the pandemic unfolded: 29% of broadband users did something to improve the speed, reliability or quality of their high-speed internet connection at home since the beginning of the outbreak.

Still, tech use has not been an unmitigated boon for everyone. “ Zoom fatigue ” was widely speculated to be a problem in the pandemic, and some Americans report related experiences in the new survey: 40% of those who have ever talked with others via video calls since the beginning of the pandemic say they have felt worn out or fatigued often or sometimes by the time they spend on them. Moreover,  changes in screen time  occurred for  Americans generally  and for  parents of young children . The survey finds that a third of all adults say they tried to cut back on time spent on their smartphone or the internet at some point during the pandemic. In addition, 72% of parents of children in grades K-12 say their kids are spending more time on screens compared with before the outbreak. 1

For many, digital interactions could only do so much as a stand-in for in-person communication. About two-thirds of Americans (68%) say the interactions they would have had in person, but instead had online or over the phone, have generally been useful – but not a replacement for in-person contact. Another 15% say these tools haven’t been of much use in their interactions. Still, 17% report that these digital interactions have been just as good as in-person contact.

Some types of technology have been more helpful than others for Americans. For example, 44% say text messages or group messaging apps have helped them a lot to stay connected with family and friends, 38% say the same about voice calls and 30% say this about video calls. Smaller shares say social media sites (20%) and email (19%) have helped them in this way.

The survey offers a snapshot of Americans’ lives just over one year into the pandemic as they reflected back on what had happened. It is important to note the findings were gathered in April 2021, just before  all U.S. adults became eligible for coronavirus vaccine s. At the time, some states were  beginning to loosen restrictions  on businesses and social encounters. This survey also was fielded before the delta variant  became prominent  in the United States,  raising concerns  about new and  evolving variants . 

Here are some of the key takeaways from the survey.

Americans’ tech experiences in the pandemic are linked to digital divides, tech readiness 

Some Americans’ experiences with technology haven’t been smooth or easy during the pandemic. The digital divides related to  internet use  and  affordability  were highlighted by the pandemic and also emerged in new ways as life moved online.

For all Americans relying on screens during the pandemic,  connection quality  has been important for school assignments, meetings and virtual social encounters alike. The new survey highlights difficulties for some: Roughly half of those who have a high-speed internet connection at home (48%) say they have problems with the speed, reliability or quality of their home connection often or sometimes. 2

Beyond that, affordability  remained a persistent concern  for a portion of digital tech users as the pandemic continued – about a quarter of home broadband users (26%) and smartphone owners (24%) said in the April 2021 survey that they worried a lot or some about paying their internet and cellphone bills over the next few months. 

From parents of children facing the “ homework gap ” to Americans struggling to  afford home internet , those with lower incomes have been particularly likely to struggle. At the same time, some of those with higher incomes have been affected as well.

Affordability and connection problems have hit broadband users with lower incomes especially hard. Nearly half of broadband users with lower incomes, and about a quarter of those with midrange incomes, say that as of April they were at least somewhat worried about paying their internet bill over the next few months. 3 And home broadband users with lower incomes are roughly 20 points more likely to say they often or sometimes experience problems with their connection than those with relatively high incomes. Still, 55% of those with lower incomes say the internet has been essential to them personally in the pandemic.

At the same time, Americans’ levels of formal education are associated with their experiences turning to tech during the pandemic. 

Those with a bachelor’s or advanced degree are about twice as likely as those with a high school diploma or less formal education to have used tech in new or different ways during the pandemic. There is also roughly a 20 percentage point gap between these two groups in the shares who have made video calls about once a day or more often and who say these calls have helped at least a little to stay connected with family and friends. And 71% of those with a bachelor’s degree or more education say the internet has been essential, compared with 45% of those with a high school diploma or less.

More broadly, not all Americans believe they have key tech skills. In this survey, about a quarter of adults (26%) say they usually need someone else’s help to set up or show them how to use a new computer, smartphone or other electronic device. And one-in-ten report they have little to no confidence in their ability to use these types of devices to do the things they need to do online. This report refers to those who say they experience either or both of these issues as having “lower tech readiness.” Some 30% of adults fall in this category. (A full description of how this group was identified can be found in  Chapter 3. )

These struggles are particularly acute for older adults, some of whom have had to  learn new tech skills  over the course of the pandemic. Roughly two-thirds of adults 75 and older fall into the group having lower tech readiness – that is, they either have little or no confidence in their ability to use their devices, or generally need help setting up and learning how to use new devices. Some 54% of Americans ages 65 to 74 are also in this group. 

Americans with lower tech readiness have had different experiences with technology during the pandemic. While 82% of the Americans with lower tech readiness say the internet has been at least important to them personally during the pandemic, they are less likely than those with higher tech readiness to say the internet has been essential (39% vs. 66%). Some 21% of those with lower tech readiness say digital interactions haven’t been of much use in standing in for in-person contact, compared with 12% of those with higher tech readiness. 

46% of parents with lower incomes whose children faced school closures say their children had at least one problem related to the ‘homework gap’

As school moved online for many families, parents and their children experienced profound changes. Fully 93% of parents with K-12 children at home say these children had some online instruction during the pandemic. Among these parents, 62% report that online learning has gone very or somewhat well, and 70% say it has been very or somewhat easy for them to help their children use technology for online instruction.

Still, 30% of the parents whose children have had online instruction during the pandemic say it has been very or somewhat difficult for them to help their children use technology or the internet for this. 

The survey also shows that children from households with lower incomes who faced school closures in the pandemic have been especially likely to encounter tech-related obstacles in completing their schoolwork – a phenomenon contributing to the “ homework gap .”

Overall, about a third (34%) of all parents whose children’s schools closed at some point say their children have encountered at least one of the tech-related issues we asked about amid COVID-19: having to do schoolwork on a cellphone, being unable to complete schoolwork because of lack of computer access at home, or having to use public Wi-Fi to finish schoolwork because there was no reliable connection at home. 

This share is higher among parents with lower incomes whose children’s schools closed. Nearly half (46%) say their children have faced at least one of these issues. Some with higher incomes were affected as well – about three-in-ten (31%) of these parents with midrange incomes say their children faced one or more of these issues, as do about one-in-five of these parents with higher household incomes.

Prior Center work has documented this “ homework gap ” in other contexts – both  before the coronavirus outbreak  and  near the beginning of the pandemic . In April 2020, for example, parents with lower incomes were particularly likely to think their children would face these struggles amid the outbreak.

Besides issues related to remote schooling, other changes were afoot in families as the pandemic forced many families to shelter in place. For instance, parents’ estimates of their children’s screen time – and family rules around this – changed in some homes. About seven-in-ten parents with children in kindergarten through 12th grade (72%) say their children were spending more time on screens as of the April survey compared with before the outbreak. Some 39% of parents with school-age children say they have become less strict about screen time rules during the outbreak. About one-in-five (18%) say they have become more strict, while 43% have kept screen time rules about the same. 

More adults now favor the idea that schools should provide digital technology to all students during the pandemic than did in April 2020

Americans’ tech struggles related to digital divides gained attention from policymakers and news organizations as the pandemic progressed.

On some policy issues, public attitudes changed over the course of the outbreak – for example, views on what K-12 schools should provide to students shifted. Some 49% now say K-12 schools have a responsibility to provide all students with laptop or tablet computers in order to help them complete their schoolwork during the pandemic, up 12 percentage points from a year ago.

The shares of those who say so have increased for both major political parties over the past year: This view shifted 15 points for Republicans and those who lean toward the GOP, and there was a 9-point increase for Democrats and Democratic leaners.

However, when it comes to views of policy solutions for internet access more generally, not much has changed. Some 37% of Americans say that the government has a responsibility to ensure all Americans have high-speed internet access during the outbreak, and the overall share is unchanged from April 2020 – the first time Americans were asked this specific question about the government’s pandemic responsibility to provide internet access. 4

Democrats are more likely than Republicans to say the government has this responsibility, and within the Republican Party, those with lower incomes are more likely to say this than their counterparts earning more money. 

Video calls and conferencing have been part of everyday life

Americans’ own words provide insight into exactly how their lives changed amid COVID-19. When asked to describe the new or different ways they had used technology, some Americans mention video calls and conferencing facilitating a variety of virtual interactions – including attending events like weddings, family holidays and funerals or transforming where and how they worked. 5 From family calls, shopping for groceries and placing takeout orders online to having telehealth visits with medical professionals or participating in online learning activities, some aspects of life have been virtually transformed: 

“I’ve gone from not even knowing remote programs like Zoom even existed, to using them nearly every day.” – Man, 54

“[I’ve been] h andling … deaths of family and friends remotely, attending and sharing classical music concerts and recitals with other professionals, viewing [my] own church services and Bible classes, shopping. … Basically, [the internet has been] a lifeline.”  – Woman, 69

“I … use Zoom for church youth activities. [I] use Zoom for meetings. I order groceries and takeout food online. We arranged for a ‘digital reception’ for my daughter’s wedding as well as live streaming the event.” – Woman, 44

When asked about video calls specifically, half of Americans report they have talked with others in this way at least once a week since the beginning of the outbreak; one-in-five have used these platforms daily. But how often people have experienced this type of digital connectedness varies by age. For example, about a quarter of adults ages 18 to 49 (27%) say they have connected with others on video calls about once a day or more often, compared with 16% of those 50 to 64 and just 7% of those 65 and older. 

Even as video technology became a part of life for users, many  accounts of burnout  surfaced and some speculated that “Zoom fatigue” was setting in as Americans grew weary of this type of screen time. The survey finds that some 40% of those who participated in video calls since the beginning of the pandemic – a third of all Americans – say they feel worn out or fatigued often or sometimes from the time they spend on video calls. About three-quarters of those who have been on these calls several times a day in the pandemic say this.

Fatigue is not limited to frequent users, however: For example, about a third (34%) of those who have made video calls about once a week say they feel worn out at least sometimes.

These are among the main findings from the survey. Other key results include:

Some Americans’ personal lives and social relationships have changed during the pandemic:  Some 36% of Americans say their own personal lives changed in a major way as a result of the coronavirus outbreak. Another 47% say their personal lives changed, but only a little bit.   About half (52%) of those who say major change has occurred in their personal lives due to the pandemic also say they have used tech in new ways, compared with about four-in-ten (38%) of those whose personal lives changed a little bit and roughly one-in-five (19%) of those who say their personal lives stayed about the same.

Even as tech helped some to stay connected, a quarter of Americans say they feel less close to close family members now compared with before the pandemic, and about four-in-ten (38%) say the same about friends they know well. Roughly half (53%) say this about casual acquaintances.

The majority of those who tried to sign up for vaccine appointments in the first part of the year went online to do so:  Despite early problems with  vaccine rollout  and  online registration systems , in the April survey tech problems did  not  appear to be major struggles for most adults who had tried to sign up online for COVID-19 vaccines. The survey explored Americans’ experiences getting these vaccine appointments and reveals that in April 57% of adults had tried to sign themselves up and 25% had tried to sign someone else up. Fully 78% of those who tried to sign themselves up and 87% of those who tried to sign others up were online registrants. 

When it comes to difficulties with the online vaccine signup process, 29% of those who had tried to sign up online – 13% of all Americans – say it was very or somewhat difficult to sign themselves up for vaccines at that time. Among five reasons for this that the survey asked about, the most common  major  reason was lack of available appointments, rather than tech-related problems. Adults 65 and older who tried to sign themselves up for the vaccine online were the most likely age group to experience at least some difficulty when they tried to get a vaccine appointment.

Tech struggles and usefulness alike vary by race and ethnicity.  Americans’ experiences also have varied across racial and ethnic groups. For example, Black Americans are more likely than White or Hispanic adults to meet the criteria for having “lower tech readiness.” 6 Among broadband users, Black and Hispanic adults were also more likely than White adults to be worried about paying their bills for their high-speed internet access at home as of April, though the share of Hispanic Americans who say this declined sharply since April 2020. And a majority of Black and Hispanic broadband users say they at least sometimes have experienced problems with their internet connection. 

Still, Black adults and Hispanic adults are more likely than White adults to say various technologies – text messages, voice calls, video calls, social media sites and email – have helped them a lot to stay connected with family and friends amid the pandemic.

Tech has helped some adults under 30 to connect with friends, but tech fatigue also set in for some.  Only about one-in-five adults ages 18 to 29 say they feel closer to friends they know well compared with before the pandemic. This share is twice as high as that among adults 50 and older. Adults under 30 are also more likely than any other age group to say social media sites have helped a lot in staying connected with family and friends (30% say so), and about four-in-ten of those ages 18 to 29 say this about video calls. 

Screen time affected some negatively, however. About six-in-ten adults under 30 (57%) who have ever made video calls in the pandemic say they at least sometimes feel worn out or fatigued from spending time on video calls, and about half (49%) of young adults say they have tried to cut back on time spent on the internet or their smartphone.

• Throughout this report, “parents” refers to those who said they were the parent or guardian of any children who were enrolled in elementary, middle or high school and who lived in their household at the time of the survey. ↩
• People with a high-speed internet connection at home also are referred to as “home broadband users” or “broadband users” throughout this report. ↩
• Family incomes are based on 2019 earnings and adjusted for differences in purchasing power by geographic region and for household sizes. Middle income is defined here as two-thirds to double the median annual family income for all panelists on the American Trends Panel. Lower income falls below that range; upper income falls above it. ↩
• A separate  Center study  also fielded in April 2021 asked Americans what the government is responsible for on a number of topics, but did not mention the coronavirus outbreak. Some 43% of Americans said in that survey that the federal government has a responsibility to provide high-speed internet for all Americans. This was a significant increase from 2019, the last time the Center had asked that more general question, when 28% said the same. ↩
• Quotations in this report may have been lightly edited for grammar, spelling and clarity. ↩
• There were not enough Asian American respondents in the sample to be broken out into a separate analysis. As always, their responses are incorporated into the general population figures throughout this report. ↩

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