Sixth Generation (6G) To Seventh (7G) Wireless Communications Visions And Standards, Challenges, Applications

The growing need for next-generation wireless networks becomes evident as the Internet of Everything (IOE) gains prominence in smart services, projecting widespread popularity in the future. While sixth generation (6G) networks have the potential to support a diverse range of IOE services, their potential limitations in meeting the demands of innovative applications point the way to seventh generation (7G) wireless systems. This article seeks to compare the characteristics of 6G and planned 7G wireless systems. Commercial development of fifth generation (5G) mobile communications systems is currently underway, introducing new services and enhancing user experiences. Despite these advancements, 5G faces challenges that require improvement. With the International Telecommunication Union Radiocommunication Sector (ITU-R) actively envisioning 6G and anticipating a consensus on 7G by October 2024, many unresolved questions persist in global discussions. This paper provides a comprehensive overview of the current understanding of 7G, exploring the vision, technical requirements, and application possibilities. It presents a critical assessment of 7G network architectures and essential technologies. In addition, the article provides an in-depth examination of advanced 7G validation platforms and existing test beds, unveiling these aspects for the first time. Future research directions and lingering issues are emphasized to contribute to the ongoing global discourse on 7G networks. Discussions on lessons learned from 7G networks culminate in the suggestion that 7G systems represent the pinnacle of mobile communication technology. Ongoing research on 7G, an intelligent cellular technology, holds promise for the future of wireless communications.

Introduction

Starting in 2020, the fifth generation (5G) of wireless communication networks will be standardized and implemented globally. Massive machine type communication (MMTC), ultra-reliable and low latency communication (URLLC), and enhanced mobile broadband (EMBB) are the three main 5G communication scenarios. Compared to fourth generation (4G) wireless communication systems, the primary features include 20 Gbps peak data rate, 0.1 Gbps user experienced data rate, 1ms end-to-end latency, support for 500 km/h mobility, 1 million devices/km2 connection density, 10 Mbps/m2 area traffic capacity, three times spectrum efficiency, and one hundred times energy efficiency. Several breakthrough technologies, including millimeter-wave (MMWAVE), massive multiple-input multiple-output (MIMO), and ultra-dense networks (UDN), have been suggested to realize the objectives of 5G. The standardization of 5G communications has been finished, and global deployment of the system is currently underway. Shows the worldwide coverage map of commercial 5G networks, incorporating field trials, testing, and research efforts. South Korea emerged as a pioneer, implementing widespread 5G deployments in approximately 85 cities with a network of 86,000 5G base stations by April 2019.

However, six cities—Seoul, Busan, Daegu, and others—were home to 85% of the 5G base stations. There, a distributed architecture was deployed using 3.5 GHz (sub-6) spectrum with data rate speeds rated between 193 and 430 Mbit/s. By the end of 2025, it is estimated that more than 65% of the world’s population will have access to 5G ultrafast 5G internet coverage. These difficulties have prompted business and academia to develop the sixth generation of wireless communication networks or 6G to meet the demands of the 2030s for communication services and to maintain the stability and competitiveness of wireless communication systems. Due to the unconventional technologies that 6G communication systems will adopt, such as a very large bandwidth (THz waves) and high AI involving operations and environments, it is anticipated that 6G communication systems will offer a large coverage that enables customers to communicate with each other everywhere at a high data rate speed.

Similar to 6G in terms of worldwide coverage, 7G mobile networks will also specify the satellite functions needed for mobile communications. Global Positioning System (GPS) will be provided by navigation satellites, Earth imaging satellites will provide additional information such as weather updates, and telecommunications satellites will handle voice and multimedia communications. Many services and local voice coverage will be supported through 6G mobile wireless networks. The next generation of mobile communications will be called 7G. Only until all standards and procedures are specified will the 7G dream come true. Perhaps it will be achieved in the generation that follows 7G and 7.5g. 6G will introduce new paradigms in wireless communication networks. To offer total coverage worldwide, 6G wireless communication networks will first integrate space-air-ground-sea networks. The coverage range of wireless communication networks will be significantly enhanced by satellite, unmanned aerial vehicles, and maritime communications. Every spectrum will be thoroughly investigated, including sub-6 GHz, mmWAVE, THz, and optical frequency bands, to offer better data rates. AI and ML technologies will be effectively integrated with 6G wireless communication networks to enable complete applications and improve network automation and management.

In addition, the performance of next-generation networks can be enhanced by the dynamic orchestration of networking, caching, and computing resources made possible by AI technology. The last but certainly not least trend in network development is the use of strong or endogenous security for both the physical and network layers. 6G wireless communication network development will be significantly aided by industry verticals such as cloud virtual reality (VR), Internet of Things (IoT) industry automation, cellular vehicle to everything (C V2X), digital twin body area networks, energy-efficient wireless network control, and federated learning systems. Provides an overview of 6G wireless networks, including performance indicators, industry verticals, supporting technologies, new paradigm shifts, and application scenarios.

6G Wireless Systems

The next generation of wireless technology is called 6G, or sixth generation wireless. Compared to 5G networks, which offer significantly increased capacity and significantly reduced latency, 6G networks will be able to use higher frequencies. Supporting communications with a latency of only one microsecond is one of the objectives of 6G networks. The speed difference between this and millisecond throughput is 1,000s. It is estimated that the market for 6G technology will enable significant advances in location awareness, presence technologies, and imaging. The combination of artificial intelligence with 6G computational infrastructure will be able to determine the optimal location for computing. Decisions about data processing, sharing, and storage will fall under this category. The fact that 6G is not yet a working technology is significant. Although some suppliers are investing in the next-generation wireless standard, industry standards for network components supporting 6G remain unchanged for years.

6G Market Statistics and Research Activities

While 5G wireless systems are still in the early stages of deployment, 6G wireless systems are projected by extensive research to meet the demands of the soon-to-be anticipated revolutionary IOE smart services. The 6G industry is expected to reach US$4.1 billion by 2030, growing at a compound annual growth rate of 70% between 2025 and 2030. Of all 6G components—edge, cloud, and AI—communications infrastructure is expected to have the largest market share, perhaps reaching US$1 billion. By 2028, there will be over 240 million AI chipsets, another essential 6G component.

6G: State-of-the-art

The future developments are as follows that need to be integrated to make 6G a reality. These are then put into the following concluding statement. Khan et al. looked at edge network-based federated learning: resource efficiency, and incentive mechanisms used for edge network-based federated learning. Its main design elements were previously proven to establish edge network-based federated learning. Some of the most important design objectives include learning algorithm design, hardware-software co-design, incentive mechanisms, and resource optimization, among others. The second was the incentive mechanism based on Stackelberg game, where they also presented some numerical results in favor of their Stackelberg game-based reward system. Finally, some open-ended research challenges and future potential directions for this work were presented. Even if the type of incentive mechanism, based on Stackelberg game, is showing encouraging results, still, it would be quite sensible to suggest an incentive mechanism from the viewpoint of contract theory.

Taxonomy

We consider emerging machine learning technologies, networking technologies, communication technologies, and key enablers. Among them, the main enablers for 6G wireless systems are edge intelligence, hemimorphic encryption, blockchain, network slicing, artificial intelligence, photonics-based cognitive radio, and space-air-ground integrated networks. Actually, this particular network slicing is considered as one of the key technologies for enablers for 5G, but the actual implementation will be used in 6G.

AI and ML Technologies: An Overview

This technology can enhance the quality of next-generation wireless networks with scalable and powerful upcoming AI and ML. The integration of mobile computing with big data led to the development of a novel field of research known as MBD, and it raises critical issues with respect to the source, analytics, applications, characteristics, and security. One of the major advantages of AI and ML is that it is driven by data. It is argued that an accurate mathematical model of most scenarios is impossible to build in 5G networks. AI and ML techniques do not apply pre-defined set rules but learn features directly from a very large collection of data to improve network efficiency and latency. Moreover, with the eventual emergence of next-generation wireless networks, it will be complex systems with different service requirements for different networks as well as different applications. Intelligent as well as self-aware networks are capable of evolution through the employment of predictive as well as adaptive AI and ML algorithms. In the classification of ANNs, the classification is defined through the capability of feed-forward as well as recurrent ANNs. It processes the massive amount of data being transmitted between devices and servers. Thus, it makes AI and ML very powerful to apply to different layers of the network. Other important uses of AI and ML approaches, besides resource allocation in big data, include proactive caching and adaptive BS, ultra-dense future wireless.

Networks witness increasing data traffic and energy consumption. All of these can be upgraded through AI and ML techniques to provide efficient and effective scheduling and allocation. There are also many uses of machine learning techniques in wireless network physical layer optimization. Traditional model-based approaches will be unable to meet the greater requirements of next-generation wireless systems, as some complex and unknown channels cannot be managed by them. Existing BB systems can redesign the decoding and detecting modules by exploiting the capability of machine learning.

Physical Layer Applications

Due to the rapid expansion of wireless communications, spectral and energy efficiency needs will increase beyond 5G. Unlike 5G, the new era physical layer will only become more complex, introducing a host of brand new difficulties. First, a communication system is too complex and has many real-world imperfections to be accurately modeled by a mathematical model. Second, collaboration between various physical layer blocks is required to overcome bottlenecks and achieve global optimality. Third, new techniques for implementing algorithms are needed to make them more realistic due to the rapidly increasing hardware complexity needed to handle novel performance difficulties.

Key 6G Technologies

We have a fascinating roadmap for future communication systems in the form of the ambitious 6G ambition. The communication system will be further developed to actualize intelligent services that combine computing, sensing, and communication with security assurances based on using all available spectra and offering users worldwide. In this sense, the 6G concept indicated earlier cannot be supported by the required 5G technology. Although many studies have been done on potential 6G required technologies, current systems are not up to par with the rapidly growing demand for 6G data services. The last undiscovered spectrum gap between the optical and MMWAVE frequency range is THz (0.1–3 Thz). Adequate frequency, wide bandwidth, adequate path loss, strong molecule absorption, lots of diffuse dispersion, and an incredibly narrow beamwidth are the characteristics of THz. Due to its strong support for ultra-high data rate services, THZ is considered one of the most promising technologies for 6G, even though actual applications are still some way off.

A. New spectrum

1) THZ: By 2024, it is expected that mobile data traffic will have grown five times. According to the 6G vision mentioned earlier, there is an increasing need for high data rate transmission and low latency services due to the accelerated expansion of video services and the introduction of new applications such as VR/AR, autonomous driving, and IoT. Most of the current 5G solutions are limited to average rates of up to 1 Gbps and are stuck in the mmWave spectrum. Overcoming issues with non-negligible spectrum congestion, 5G communication

2) Novel channel research: The four steps of traditional channel research are usually channel measurement, channel modeling, channel characteristic analysis, and channel parameter estimation. This passive method of channel recognition has various drawbacks. Channel measurement requires a lot of labor, money, and time. In addition, all frequency ranges or scenarios can never be covered by channel measurements in practice. The estimation of channel parameters is further complicated by the substantial amount of data and the high computational complexity. Analyzing channel characteristics is limited to known conditions and frequencies.

3) Space channel capacity: Wireless propagation channel modeling theory and antenna theory combine these two ideas. Specifically, the wireless propagation channel combines information theory with EM theory because it originates from antennas and uses EM waves to carry information. Figure 12 shows how these traditional ideas are related to each other. Since electromagnetic waves (EM waves) are the source of channel capacity deficiency, EM theory is an important part of wireless communication systems. However, academics studying wireless communications have not paid significant attention to information theory research. It should be noted that while the core technologies of 6G present opportunities and challenges for the fusion of different theories, they also face the limitations of individual theories.

6G must achieve continuous full-space CSI to meet new technical criteria. The near-field range is expanding with the introduction of 6G new antenna technology due to the increase in antenna size and number of units. For example, short-wave communication antennas can reach tens of meters in size, and they are inextricably linked to their communication environment. In addition, when signal sources shift from discrete to continuous, the unit spacing of the antenna decreases, placing additional demands on how channels are represented. The number of users of 6G wireless communication networks is expected to increase as it grows from local terrestrial coverage to global space air-ground-sea integrated network coverage. To inform generalized antenna design and the construction of continuous full-space wireless channel maps, 6G wireless communication networks exhibit a development trend from discrete space to continuous full space. To that end, CSI at any point in continuous full space must be obtained, and the channel capacity must be calculated.

Conclusion

To meet the upcoming challenges posed by the sharp increase in wireless data traffic during the global deployment of 5G networks, industry and academic collaborations have begun to design the next generation of wireless communication systems, or 6G. Along with a host of new services, 6G technology enables bitrates of up to Tbps with latency of less than 1ms. To promote future 6G in the following areas: energy efficiency, intelligence, spectral efficiency, security, privacy, confidentiality, affordability, and optimization, this study began by outlining a vision and essential elements. Next, we talked about various potential barriers associated with 6G technology and possible ways to support future 6G. International research initiatives that want to develop a vision for future 6G should complete this task. Examine 5G and 6G wireless technologies and create a chart outlining the major distinctions between them. Finally, 7G introduces wireless technology, which can operate at higher frequencies and offer significantly greater capacity and lower connection latency. The seventh generation of wireless technology, or 7G, will primarily focus research on mobile communication networks. Future research on 7G technology should focus on identifying its advantages over existing wireless systems.

Read Also:

1. Towards 6G: Future Communication Technology
2. General Architecture Of Wireless Technology
3. 6G Technology
4. Cell-Phone Technology
5. 6G and 7G Cellular Network Technology

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