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6G Mobile Communication Network: Vision, Challenges and Key Technologies

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Abstract and Figures

With the open of the scale-up commercial deployment of 5G network, more and more researchers and related organizations began to consider the next generation of mobile communication system. This article will explore the 6G concept for 2030s. Firstly, this article summarizes the future 6G vision with four keywords: "Intelligent Connectivity", "Deep Connectivity", "Holographic Connectivity" and "Ubiquitous Connectivity", and these four keywords together constitute the 6G overall vision of "Wherever you think, everything follows your heart ". Then, the technical requirements and challenges to realize the 6G vision are analyzed, including peak throughput, higher energy efficiency, connection every where and anytime, new theories and technologies, self-aggregating communications fabric, and some non-technical challenges. Then the potential key technologies of 6G are classified and presented: communication technologies on new spectrum, including terahertz communication and visible light communication; fundamental technologies, including sparse theory (compressed sensing), new channel coding technology, large-scale antenna and flexible spectrum usage; special technical features, including Space-Air-Ground-Sea integrated communication and wireless tactile network. By exploring the 6G vision, requirements and challenges, as well as potential key technologies, this article attempts to outline the overall framework of 6G, and to provide directional guidance for the subsequent 6G research. ( If you are interested in 6G key technologies, please refer to our latest article “ Potential Key Technologies for 6G Mobile Communications ” View online: )
G Vision  Intelligent connectivity Artificial Intelligence (AI) is one of the hottest topics at present, and almost all fields are exploring the use of AI technology. The combination of wireless mobile communication network and AI to make AI better enabling network has also become an inevitable trend [14]-[30]. At present, people have begun to try to use AI technology in 5G system[31]-[32], but the current combination of 5G and AI can only be regarded as the optimization of traditional network architecture using AI, rather than a new intelligent communication network system based on AI. Firstly, the application of AI technology in 5G network is relatively late. It was not until recent years that we really started to study and try to apply AI technology in 5G network, and the 5G network architecture itself has already been finalized. Although the design of 5G network architecture initially considered enough flexibility (so-called software definable), it did not consider AI technology after all, so it is still a traditional network architecture. Secondly, although the AI technology is developing very fast and has also demonstrated its strong ability in some areas, but it is still in the exploratory stage in more fields. The research on the combination of AI and wireless communication technology is just beginning, and a long-term research process is needed before the real technology matures. However, the trend of AI shows us the possibility of technology maturity in the next decade. At the same time, considering that the future 6G network structure will be more and more huge and heterogeneous, and the business types and application scenarios will become more and more complex and changeable, it is almost inevitable to make full use of AI technology to solve this complex demand. It is expected that in the future 6G will break through the application scope of traditional mobile communication systems and become the basic Internet supporting the operation of the whole society and the whole field/industry. If the future network still uses the existing unified communication network framework to support the extremely diverse and complex applications in 6G era, it will face unprecedented challenges. A new round of revival and rapid development of AI technology has provided potential possibilities for meeting the above challenges and surpassing the traditional mobile communication design concepts and performance, and will fully enable the future 6G network [21]. Therefore, we believe that building 6G network based on AI technology will be an inevitable choice, and "Intelligent" will be the inherent feature of 6G network, namely the so-called "Intelligent connectivity". The characteristic of "Intelligent Connectivity" can be expressed as the inherent
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6G Mobile Communication Network: Vision, Challengesand
Key Technologies
Yajun ZHAO1*, Guanghui YU2, Hanqing XU1
1. Algorithm Dept., Wireless Product R
D Institute, ZTE Corporation, Beijing 100029, China;
2. Algorithm Dept., Wireless Product R
D Institute, ZTE Corporation, Shenzhen 518055, China.
* Corresponding author. E-mail:
Abstract With the open of the scale-up commercial deployment of 5G network, more and more researchers and
related organizations began to consider the next generation of mobile communication system. This article will
explore the 6G concept for 2030s. Firstly, this article summarizes the future 6G vision with four keywords:
"Intelligent Connectivity", "Deep Connectivity", "Holographic Connectivity" and "Ubiquitous Connectivity", and
these four keywords together constitute the 6G overall vision of "Wherever you think, everything follows your
heart ". Then, the technical requirements and challenges to realize the 6G vision are analyzed, including peak
throughput, higher energy efficiency, connection every where and anytime, new theories and technologies,
self-aggregating communications fabric, and some non-technical challenges. Then the potential key technologies
of 6G are classified and presented: communication technologies on new spectrum, including terahertz
communication and visible light communication; fundamental technologies, including sparse theory (compressed
sensing), new channel coding technology, large-scale antenna, flexible spectrum usage and AI-based wireless
communication; special technical features, including Space-Air-Ground-Sea integrated communication and
wireless tactile network. By exploring the 6G vision, requirements and challenges, as well as potential key
technologies, this article attempts to outline the overall framework of 6G, and to provide directional guidance for
the subsequent 6G research.
Keywords 6G, vision, terahertz, VLC, compressed sensing, free duplex, wireless tactile network
1 Introduction
With the completion of the first standard version of 5G, there will be a small-scale
commercial trial of 5G network equipment in 2019, and the first batch of 5G-compliant terminals
will also be on the market. It can be expected that the 5G wireless mobile communication system
with three major technical features (enhanced Mobile BroadBand, eMBB; massive
Machine-Type-Communications, mMTC; ultra-Reliable Low-Latency Communications, uRLLC)
will support the wireless communication needs of the information society in the next decade
(2020-2030), becoming the largest and most complex communication network ever. 5G will
profoundly affect social development and human life in many aspects: With water and electricity,
mobile communication will become the basic demand of human society; become the driving force
to promote social structure changes including social economy, culture and daily life; and will
greatly expand the scope of human activities.
Citation:Zhao Y J, Yu G H, Xu H Q. 6G Mobile Communication Network: Vision, Challenges and Key Technologies (in Chinese). Sci Sin
Inform, ISSN 1674-7267, Pre-published , ( )
Yajun ZHAO, et al. 6G Mobile Communication Network: Vision, Challenges and Key Technologies
Of course, the 5G vision mentioned above also need technical personnel in the field of
communication and other related professionals to work together after a certain period of time and
gradually realize, including the continuous improvement of standards, gradual landing of
engineering and breakthroughs in commercial application modes. Here, we will observes the
process of continuous maturity and perfection of 5G standard from the standpoint of
At present, it is in the first stage of 5G standardization, namely 5G based function
standardization stage In this stage including 5G NR Rel-15 and Rel-16 standard versions, we
mainly focus on the optimization of eMBB technical characteristics, taking into account the basic
requirements of uRLLC and mMTC. The first basic standardized version of 5G (5G NR Rel-15)
has been basically completed, including three sub-versions released in stages: the first 5G
technical standard issued by the International Organization for Standardization (ISO) 3GPP in
March 2018 to support non-standalone (NSA) and eMBB functions [1]; in September 2018, 3GPP
approved 5G Standalone (SA) technical standard [2], and 5G has entered a new stage of industrial
sprint since then; in December 2018, 3GPP announced at the RAN plenary meeting that the last
sub-version (5G NR Rel-15 late drop) will be released in March 2019 to support the feature of
NR-NR DC (Dual Connectivity)[3]. The second standard version of 5G (Rel-16), whose technical
features have been approved by the standard, is in full swing and will be completed and officially
released in December 2019.
The next stage of 5G standardization (called "5G+") will start in 2020. The corresponding
standard versions include 5G NR Rel-17 and subsequent versions. The standardization in the
phase of 5G+ will focuse on two aspects [4]: optimizing the Internet of Things (IoT)
characteristics of uRLLC and mMTC to better support applications in vertical industries (e.g.,
industrial wireless Internet, high-speed rail wireless communication, etc.); designing and
supporting the characteristics of the millimeter bands with 52.6 GHz-114.25 GHz It is expected
that the second stage of 5G standardization will attract more members of the vertical industry to
participate in the formulation of standards, so that 5G standards can better meet the needs of the
vertical industry.
Although 5G is still in the initial stage of commercial scale, i.e., the related technical
characteristics need to be further improved and the business model of Internet of Things and
vertical industry application scenarios need to be further explored, it is also necessary for us to
synchronously look forward to the communication needs of the future information society and
start the concept and technology research for the next generation mobile communication system.
Here we try to analyze the necessity of the immediate start-up of the concept and technology
research on the next generation mobile communication system (hereinafter referred to as 6G) from
three aspects. (1) Ten-year cycle law. "Since the introduction of the first generation (1G) mobile
communication system in 1982, each generation of wireless mobile communication system has
been updated every ten years" [5]. Moreover, it takes about ten years for any generation to start
conceptual research and commercial application, that is, when the previous generation enters the
commercial period, the next generation begins conceptual and technical research. To start 6G
research now is in line with the development law of mobile communication system since 5G
research started ten years ago. (2) Catfish effect. Unlike previous generations of mobile
communication systems, 5G is mainly aimed at Internet of Things/vertical industry application
scenarios. With the large-scale commercial deployment of 5G network, especially in the middle
and late stages of 5G, there will be many members of vertical industry deeply involved in 5G
ecology. Compared with the status quo dominated by traditional operators, the in-depth
participation of emerging enterprises (especially Internet companies born with innovative thinking)
in the future will have a huge impact on the traditional telecommunications industry, or even
revolutionary impact, namely the so-called "catfish effect". (3) The explosive potential of IoT
business model. Just as the emergence of smartphones stimulated 3G applications and triggered
the demand for large-scale deployment of 4G, it is believed that some modes of IoT business will
also stimulate the outbreak of 5G industry at some point in the 5G era, thereby stimulating the
demand for the future 6G network. We need to have enough imagination, and prepare for the
possible arrival of the future network in advance to lay a good technical foundation. In summary,
we can draw the conclusion that it is the right time to start the research of the next generation
wireless mobile communication system (6G).
Recently, more and more institutions or individuals, including academia, industry,
government and even the public [6] - [9], have begun to involve B5G/6G concepts. According to
the statistics of Google search, "6g technologies" is one of the 17 keywords with the largest search
volume today. At the 2018 Mobile World Congress, an official of the Federal Communications
Commission looked ahead to 6G [9] in public. Not only the United States, China also has
launched 6G related work. In an interview with the media in March 2018, Miao Wei(Minister of
Industry and Information Technology) said that China had begun to study 6G [11]. In addition to
China and the United States, it is reported that European Union, Russia and other countries are
also closely carrying out relevant work. It can be seen from these that there is a certain consensus
on starting 6G related research now.
This paper will mainly discuss the communication requirements and technologies in the next
decade (2030~), that is, for the next generation wireless mobile communication system (6G). 6G
will be a revolutionary system comparing 5G. Of course, it is not excluded the possibility that
some of the technical features will mature ahead of time or some business scenarios will be
applied ahead of time involved in this paper, and then these parts can be attributed to the so-called
B5G (Beyond 5G, i.e.5G Evolution). It can be expected that most of the current 5G features will
continue to be retained and enhanced in 6G systems, but these 5G technology enhancements do
not fall within the scope of this article. This paper will focus on the key revolutionary technologies
that may be introduced into 6G system.
This paper will focus on the 6G vision, requirements and challenges, potential candidate
technologies, and try to outline the overall framework of 6G, in order to provide direction for the
follow-up study of 6G. The following chapters are structured as follows: Chapter 2, Imagine the
vision and challenges of 6G; Chapter 3, Explore potential key technologies for 6G; Finally,
Chapter 4 gives a summary of the full text.
2 6G Vision and Challenge
In the initial stage of 5G start-up, the established vision of 5G is "information is at your
disposal, everything is at your fingertips" [12]. Based on this vision, the requirements of 5G
technical indicators are determined, and candidate key technologies are further proposed. After the
process of concept determination, technology research, standardization and product development,
5G system will be put into commercial use on a large scale, and the 5G vision will be gradually
realized with the improvement of standards and the maturity of industry. It is also necessary to
Yajun ZHAO, et al. 6G Mobile Communication Network: Vision, Challenges and Key Technologies
establish the 6G vision and the corresponding technical requirements and challenges in order to
initiate the 6G prospective research so as to tract the follow-up 6G related research. However, 5G
has been so exciting and will fully empower society, then what can we do in the future?
This chapter will first give the imagination on 6G vision, and analyze the necessity of the
vision, and then further expounds the technical requirements and challenges in realizing the 6G
2.1 6G Vision
At present, the goal of 5G is to penetrate into all fields of society and build an all-round
information ecosystem centered on users. However, due to the limited standardization time and the
maturity of related technology development, there are still many deficiencies in the spatial depth
and breadth of information exchange: the current communication objects are concentrated in the
limited space range of thousands of meters above the land surface; although considering the
requirements of Internet of Thing, there is still a long way to go from the real ubiquitous Internet
of Thing. Especially with the rapid expansion of the scope of human activities and the rapid
progress of many technical fields, there is a higher demand for more extensive and diverse
information interaction.
The goal of 6G is to meet the needs of the information society ten years later (2030 ~), so the
6G vision should be those needs that 5G can not meet and need to be further upgraded. Based on
the demand that 5G can meet and the development trend of other related fields, we think that 6G
vision can be summarized into four key words (see Figure 1): "Intelligent Connectivity", "Deep
Connectivity", "Holographic Connectivity" and "Ubiquitous Connectivity". These four keywords
together constitute the 6G overall vision of "Wherever you think, everything follows your heart".
The 5G vision is "information is at your heart, everything is at your fingertips". It emphasizes
information exchange, everything can be connected, and the connecting objects are concentrated
in a limited space of 10 km above the land. Although 5G started to study and standardize the
technical characteristics of non-terrestrial networks (NTN) in Rel-16, the standard and technical
system of satellite communication network and cellular network involved in NTN architecture are
still independent of each other, and need to connect and interact through special gateway
equipment[13]. Its communication capability and efficiency can hardly meet the "ubiquitous
connectivity" requirement after ten years. In order to meet the needs of ubiquitous connectivity in
the future, 6G needs to introduce the space-air-ground-sea integration network described below.
This network will be an organic whole, that is, it needs a unified standard protocol architecture
and technical system to truly realize the ubiquitous connectivity of space-air-ground-sea
integration. In addition, 5G mMTC emphasizes the number of connections rather than real-time
performance; URLLC emphasizes reliability and real-time performance, but does not require the
number and throughput of connections, which is achieved at the cost of reducing spectral
efficiency and number of connections. The 6G vision requires massive connectivity, reliability,
real-time and throughput requirements, which are new and huge challenges to communication
networks. The typical scenario is wireless tactile networks described below. Therefore, although
some of the basic concepts covered by 6G vision are already involved in 5G, 6G vision puts
forward higher goals to meet the needs of new scenarios in the future.
Figure 1 6G Vision
Intelligent connectivity
Artificial Intelligence (AI) is one of the hottest topics at present, and almost all fields are
exploring the use of AI technology. The combination of wireless mobile communication network
and AI to make AI better enabling network has also become an inevitable trend [14]-[30]. At
present, people have begun to try to use AI technology in 5G system[31]-[32], but the current
combination of 5G and AI can only be regarded as the optimization of traditional network
architecture using AI, rather than a new intelligent communication network system based on AI.
Firstly, the application of AI technology in 5G network is relatively late. It was not until recent
years that we really started to study and try to apply AI technology in 5G network, and the 5G
network architecture itself has already been finalized. Although the design of 5G network
architecture initially considered enough flexibility (so-called software definable), it did not
consider AI technology after all, so it is still a traditional network architecture. Secondly, although
the AI technology is developing very fast and has also demonstrated its strong ability in some
areas, but it is still in the exploratory stage in more fields. The research on the combination of AI
and wireless communication technology is just beginning, and a long-term research process is
needed before the real technology matures.
However, the trend of AI shows us the possibility of technology maturity in the next decade.
At the same time, considering that the future 6G network structure will be more and more huge
and heterogeneous, and the business types and application scenarios will become more and more
complex and changeable, it is almost inevitable to make full use of AI technology to solve this
complex demand. It is expected that in the future 6G will break through the application scope of
traditional mobile communication systems and become the basic Internet supporting the operation
of the whole society and the whole field/industry. If the future network still uses the existing
unified communication network framework to support the extremely diverse and complex
applications in 6G era, it will face unprecedented challenges. A new round of revival and rapid
development of AI technology has provided potential possibilities for meeting the above
challenges and surpassing the traditional mobile communication design concepts and performance,
and will fully enable the future 6G network [21]. Therefore, we believe that building 6G network
based on AI technology will be an inevitable choice, and "Intelligent" will be the inherent feature
of 6G network, namely the so-called "Intelligent connectivity".
The characteristic of "Intelligent Connectivity" can be expressed as the inherent
Yajun ZHAO, et al. 6G Mobile Communication Network: Vision, Challenges and Key Technologies
intellectualization of communication systems: intellectualization of network elements and network
architecture, intellectualization of connecting objects (intellectualization of terminal devices), and
information support of intellectualized services. In the future, 6G networks will face many
challenges: more complex and huge networks, more types of terminals and network devices, and
more complex and diverse business types. "Intelligent Connectivity" will meet two requirements
at the same time: on the one hand, all the related connected devices in the network itself are
intelligent, and the related services have been intelligent; on the other hand, the complex and huge
network itself needs intelligent management. "Intelligent Connectivity" will be the basic
characteristics supporting the other three major features of 6G network: Deep Connectivity,
Holographic Connectivity and Ubiquitous Connectivity.
Deep Connectivity
Traditional cellular networks (including 5G networks to be deployed on a large scale) have
the concept of deep coverage, mainly to optimize the deep coverage of indoor access requirements.
In order to achieve deep indoor coverage, outdoor macro base stations are usually used to cover
indoor or deploy wireless nodes indoors. 4G and previous generations of cellular network systems
are aimed at people-centered communication needs, and deep coverage is optimized for typical
indoor scenarios of human activities. After the technology evolution and engineering experience
accumulation of multi-generation wireless communication system, the optimization technology of
typical indoor scene coverage for human activity sites has been very mature. Starting from 5G, the
object of communication has expanded from human-centered communication to the simultaneous
communication of things, that is, the so-called interconnection of all things. Therefore, the design
and deployment of 5G and future wireless communication networks need to take into account both
the deep coverage requirements of people and objects, especially the deep coverage of the ITU
With the expansion of human production and living space, the types and scenarios of
information exchange demand are becoming more and more complex. With 5G as the starting
point, the interconnection of all things will promote the rapid growth of Internet of Things
communication demand, and it is likely to erupt in the next few years. Relative to the
communication needs of personnel, the information exchange in the Internet of Things will be
greatly expanded in both spatial scope and information interaction type. It can be expected that in
the future, the demand of the Federation of Things will develop rapidly in several aspects: (1) the
deep expansion of the connecting object activity space. (2) Deeper perceptual interaction. In the
future, most of the communication devices and their connected objects will be intellectualized,
which requires deeper perception, more real-time feedback and response, such as extended human
trunk and limbs; (3) deep data mining in the physical network world. AI/deep learning will deeply
mine and utilize the data of future communication networks, and also include the large data
communication requirements to support deep learning; (4) in-depth nerve interaction. With the
maturity of technology such as Brain Computer Interface (BCI), direct interaction between
thinking and thinking will become possible, and a certain degree of "telepathy" will probably
become a reality [10] [34]. Therefore, we expect that in the next 10 years (2030 ~) of 6G systems,
access requirements will evolve from deep coverage to "Deep connectivity". Its characteristics can
be summarized as follows:
Deep Sensing: Tactile Internet;
Deep Learning/AI: Deep Data Mining;
Deep Mind: Telepathy, Mind-to-Mind Communication.
Holographic Connectivity
AR/VR (Virtual and Augmented Reality) is considered to be one of the most important
requirements of 5G, especially for one of the typical applications with high throughput
requirements of 5G. 5G will be able to support the transformation of AR/VR of current wired or
fixed wireless access into wireless mobile AR/VR of broader scenarios. Once AR/VR can be used
more easily and conveniently without location restriction, it will promote the rapid development of
AR/VR services, and then stimulate the rapid development and maturity of AR/VR technology
and equipment itself. It can be expected that in ten years (2030 ~), the media interaction will be
mainly planar multimedia, high fidelity AR/VR interaction, even holographic information
interaction, and wireless holographic communication will become a reality. High fidelity AR/VR
will be ubiquitous, and holographic communication and display can also be carried out at any time
and anywhere, so that people can enjoy fully immersed holographic interactive experience at any
time and place, that is, to realize the communication vision of so-called "holographic
connectivity". Of course, if we want to achieve holographic communication and high fidelity
AR/VR based on wireless communication network, we will face many challenges [35]. A series of
literatures have been studying the use of AI technology to solve the related problems [36] - [38],
which requires the support of "Intelligent connectivity".
Holographic connectivity can be summarized as: holographic communication, high fidelity
AR/VR, AR/VR with seamless coverage anytime, anywhere.
Ubiquitous Connectivity
Traditional cellular networks also have the need for wireless access anywhere and anytime.
However, as mentioned earlier, the 5G system will greatly expand the space scope and the type of
information exchange in the Internet of Things, relative to the communication requirements of
people. The range of activities of the equipment will greatly expand the geographic space of
communication access, including unmanned detectors deployed in the deep, deep sea or deep
space, human/unmanned aerial vehicles in the middle and high altitude, autonomous robots in the
harsh environment, intelligent remote control equipment and so on. In addition, with the rapid
development of science and technology in the fields of astronautics, deep-sea exploration and
other fields, and the improvement of survival ability in some extreme natural environments,
human activity space is also expanding rapidly. For example, in 2030-2040, there may be more
opportunities for people to enter outer space, and the communication needs between satellites and
the ground, between satellites and between spacecrafts will be more common than the special
communication needs limited to a few professional fields of scientific exploration, and the traces
of human activities on the ground will be more likely to appear in the polar, desert hinterland, etc.
More uninhabited islands enter the human race. The above communication scenarios constitute a
broader "anytime, anywhere" connection requirement ten years later (2030 ~), that is, to achieve
real "Ubiquitous connectivity", "a vast" world will become more and more accessible.
The characteristic of “Ubiquitous Connectivity” can be summarized as follows:
three-dimensional coverage and connection to all types of terrain and space, which means the
connection of anytime and anywhere, i.e. Integration of Space-Air-Ground-Sea communication.
Comparing with "Deep Connectivity" and "Ubiquitous Connectivity", the former emphasizes the
depth of the connected object, while the latter emphasizes the breadth of the distributed area of the
Yajun ZHAO, et al. 6G Mobile Communication Network: Vision, Challenges and Key Technologies
connected object.
Summarizing the above four future 6G visions, "Intelligent Connectivity" is the brain and
nerve of the 6G network, while the other three characteristics of "Deep Connectivity",
"Holographic Connectivity" and "Ubiquitous Connectivity" constitute the trunk of the 6G network.
These four characteristics together make the future 6G network a complete organic whole with
"soul". In the future, the communication system will be further developed and enhanced on the
basis of the existing 5G. The information will break through the limitation of time and space, the
network will close the distance between all things, the seamless integration of human and all
things will be realized, and finally the 6G overall vision, "Wherever you think, everything
follows your heart", will be achieved.
2.2 Requirements and Challenges
Chapter 2.1 above provides a wonderful imagination for the future 6G network. But if we
want to realize these good visions, we will have to face many technical requirements and
challenges. Undoubtedly, most of the Key Performance Indicators (KPIs) of 5G will be further
improved on the basis of existing demand, including higher throughput, lower delay, higher
reliability and larger number of connections. However, this article will focus on several key
technical requirements and challenges specific to 6G. This section will first list these key technical
requirements and challenges of 6G, and then discuss and analyze them in detail.
In order to realize the vision of 6G network and meet future communication needs, the
following key technical requirements and challenges need to be considered (Figure 2).
Figure 2 6G Requirements and Challenges
Peak Rate-Terabit Era
When referring to wireless mobile communication systems, the first requirement that people
should consider is peak rate, which is one of the key technical indicators that the first generation
of wireless mobile communication systems have been pursuing since its inception. There is no
doubt that 6G will also further increase the peak rate. From the perspective of wireless
communication system development law and 6G vision, we can see that 6G peak rate may enter
the Terabit Era (Tb/s).
Firstly, we quantitatively predict the peak rate demand in 10 years (2030 ~) based on the
statistical law of peak rate rise in 1-5G mobile communication system. Based on the analysis of
reference [44], it can be seen that the growth of peak rate of 1-5G mobile communication system
obeys exponential distribution (calculated according to the standardized time point of each
generation system). Based on the peak rate corresponding to the peak rate shown in the second
column of Table 1 in this paper (the peak rate of 1-5G mobile communication system), the
development trend of the next decade is predicted, and it can be concluded that the peak rate of
Tb/s may reach in 2030. Secondly, from the qualitative analysis of 6G vision, it can be seen that
there are at least two applications that need a significant increase in 6G peak rate: (1) intelligent
applications (Big-Data based) require massive data transmission. Intelligent application (Big-Data
based) may be an important driving force for the development of the next generation mobile
communication system; (2) high fidelity AR/VR and holographic communications will be the
inevitable applications supported by 6G, and the data rate required will be much higher than other
wireless applications we currently know.
Furthermore, in order to achieve high fidelity immersive AR/VR, not only the peak rate of
Tb/s, but also the lower interaction delay, i.e., both high throughput and low delay, are required. In
addition, AR/VR anytime and anywhere means that we want to meet the high-speed demand at
any time and anywhere, which requires not only super-high peak rate, but also super-high
coverage performance.
Summarizing the above analysis, we can see that the peak rate of 6G network will up to Tb/s.
In addition, not only the peak rate requirement of local coverage areas (such as hot spots), 6G
network will also require the connections with high-speed and low-latency at any time and
anywhere. which will be a huge challenge for 6G network.
Higher Energy Efficiency
Ultra-large-scale mobile communication network has become an indispensable part of the
world's energy consumption. It not only produces huge carbon emissions, but also occupies a
considerable part of the operating costs. In the future, 6G networks will have ultra-high throughput,
ultra-large bandwidth and ultra-large number of ubiquitous wireless nodes, which will bring
unprecedented challenges to energy consumption. Spectrum efficiency and spectrum bandwidth
increases, throughput can be increased greatly, but the energy efficiency problem will be more
serious. We have to reduce energy consumption per bit (J/bit) as far as possible. The ubiquitous
and dense sensors of wireless sensing network filled with human production and living space will
bring two energy consumption problems: first, the huge number of sensors will bring high total
energy consumption; second, how to supply energy conveniently and effectively for ubiquitous
deployment is also a challenge. In addition, massive data processing power consumption for
"Intelligent connectivity" and ultra-large antenna processing power consumption are also the
challenges of power consumption faced by future 6G networks. Faced with the huge energy
consumption pressure of the future 6G network, green energy-saving communication is
particularly important and urgent [45].
Connection Everywhere and Anytime
With the progress of science and technology, the space of human activities will be further
expanded, and the active areas will reach high altitude, outer space, ocean and deep sea more
generally. Communication nodes, especially the IoT nodes, will be spread over a wider area than
the personnel.. Communication network has been inseparable from human social activities. In the
future, we need to build a future network, which owns the characteristics of Omnipresent
(Covering the space, air, groud and sea), All-in-one (Internet of Everything), Omniscience (with
Yajun ZHAO, et al. 6G Mobile Communication Network: Vision, Challenges and Key Technologies
the help of various sensors), All-purpose (Based on big data and deep learning), to truly realize
the connection and interaction needs at any time and anywhere. The communication goal of future
communication network should be: Anyone can communicate with Anyone or interact with any
related object at any time and anywhere [46].
New Theories and Technologies
In order to realize the challenging vision of 6G, more available spectrum resources need to be
added. At the same time, some basic theories and technologies need to be broken through. Based
on the requirement analysis of 6G vision, we believe that breakthroughs need to be made in
several key areas, including new signal sampling mechanism, new channel coding and modulation
mechanism, terahertz communication theory and technology, AI-based wireless communication
theory and technology.
Self-Aggregating Communications Fabric
Almost every generation of 3GPP standards claims to be able to integrate a variety of
technical standards, but in the end, they are all self-enclosed standard systems. Although the 3GPP
standard tries to do everything all by itself, in the gradual realization of the interconnection of all
things, we will have to face the problem of integration with other complicated and vertical
industry standards and technologies. In order to better support the interconnection of all things and
vertical industry applications, 6G should really be able to dynamically integrate a variety of
technology systems, with the ability of intelligent dynamic self-aggregation for different types of
networks (technologies). Although 5G can adapt to different types of networks (technologies) to a
certain extent, it can only be combined in static or semi-static mode. 6G will need to aggregate
different types of networks (technologies) in a more intelligent and flexible way to dynamically
and adaptively meet complex and diverse scenarios and business needs.
Nontechnical Challenges
If the 6G is to land smoothly in the future, it will not only face the challenges of the
above-mentioned technical problems, but also have to overcome the challenges of many
non-technical factors, such as trade barriers, consumer habits, policies and regulations.
Compared with 5G, 6G will penetrate into all aspects of social production and life more
comprehensively, and will be more closely integrated with other vertical industries. This means
that mobile communication is no longer confined to its own field, and needs to work closely with
other vertical industries/fields. However, the inherent behavior or interest relationship of some
traditional industries will directly or indirectly set up industry barriers to the entry of mobile
Spectrum allocation and usage rules are another non-technical constraint. For example, to use
the terahertz spectrum well in 6G system requires the coordinated allocation of different countries
and regions around the world to allocate a uniform band range as far as possible, while also
considering coordination with users of the spectrum in other areas, such as meteorological radar.
Satellite communications will face more restrictions of policies and regulations. Firstly, the
orbit and spectrum resources used in satellite communications need to be solved through
consultation among all countries. Secondly, compared with traditional ground communications,
satellite communications will face more challenges in global roaming handover. At present,
several major countries and some commercial entities are actively building satellite
communication systems. How to coordinate these independently deployed satellite communication
systems will be a very complex problem.
In addition, after mobile communication has entered many vertical industries with completely
different characteristics, it has to face the user usage habits with great differences. It will be a very
challenging problem to change the inherent ways of thinking and habits of users in these diverse
vertical industries more quickly and to adapt to the new ways and rules of behavior as soon as
The 6G vision is exciting, and the key candidate technologies of 6G are full of challenges.
The 6G network will eventually provide terabit rate per second, support an average of 1000 +
wireless nodes per person in 10 years (2030 ~), and provide instant holographic connectivity
anytime and anywhere. The future will be a completely data-driven society in which people and
things are connected universally, almost instantaneously (milliseconds) to form an incredibly fully
connected utopian world.
3 6G Potential Key Technologies
The development of wireless access technology mainly comes from two aspects: key
theory/technology breakthroughs to promote technology development, and application
demand-driven technology development. As to the potential key technologies of the future 6G,
different organizations give different opinions [6] - [10]. At present, the concept of 6G is still in
the early stage of discussion, and the views given by various countries are quite different.
However, I believe that with the in-depth discussion of 6G concept and technical research, the
understanding will gradually become clear, and the research direction will continue to converge
and focus. This chapter will first classify and list the potential key candidate technical
characteristics of 6G, and then analyze and interpret the relevant candidate technical
In order to realize the 6G vision and challenges described in Chapter 2, taking into account
the development status and trends of related technologies, we believe that the potential key
technical features of 6G can include the following aspects (Figure 3).
Figure 3 6G Potential Key Technologies
Basic technology is the cornerstone of 6G network. Only when the key basic technology is
broken through, the corresponding technical needs of 6G network can be met, and the related
vision can be realized. The proprietary technology features are organically composed of several
Yajun ZHAO, et al. 6G Mobile Communication Network: Vision, Challenges and Key Technologies
key basic technology points to meet the needs of future 6G typical scenarios. From the system
dimension, many key technology points constitute proprietary technology characteristics, while
many proprietary technology characteristics combine to build an organic system. At present, we
need to make basic research and breakthroughs in 6G candidate key technologies, laying the
foundation for standardization of future 6G networks and technical research of Engineering
realization. Among them, the AI-based Wireless communication is very hot in recent years, and it
is also the key technology to realize the Intelligent Connectivity of the future 6G network. But
whether it can be used as the basic technology in the wireless field is still controversial.
3.1 Communication Technologies on New Spectrum
Spectrum is the basis and scarce resource of mobile communication. The growing demand
for traffic requires future mobile communication systems to expand available spectrum resources.
Terahertz and Visible Light will be two kinds of attractive candidate spectrum. The development
and utilization of terahertz spectrum in communication and other fields has been highly valued by
countries and regions from Europe, the United States, Japan and other countries. It has also
received strong support from the International Telecommunication Union (ITU). Visible light
communication technology is a new communication mode developed with the support of
high-speed switch by lighting source. It can effectively alleviate the current problem of radio
frequency communication bandwidth tension, and provide a new choice for short-distance
wireless communication.
This section will analyze the spectrum characteristics of terahertz and visible light, discuss
their main application scenarios, and present the technical challenges they face.
3.1.1 THz Communication
Terahertz wave refers to the electromagnetic wave whose spectrum is between 0.1 and 10
THz and whose wavelength is 30 to 3000 microns. The spectrum is between microwave and
far-infrared light, adjacent to millimeter wave in its low band, and adjacent to infrared light in its
high band, located in the transition region between Macroelectronics and micro-photonics.
Terahertz, as a new frequency band between microwave and optical wave, has not been fully
developed. Terahertz communication has the advantages of rich spectrum resources and high
transmission rate. It is a very advantageous broadband wireless access (Tb/s level communication)
technology in future mobile communications[47]. Jessica Rosenworcel, Commissioner of the
Federal Communications Commission of the United States, said at the World Mobile
Communications Congress in September 2018 that 6G could adopt THz-based spectrum-based
network and spatial multiplexing technology [9].
Because of its unique characteristics, terahertz communication has many advantages over
microwave and wireless optical communication, which determines that terahertz wave has broad
application prospects in high-speed short-distance broadband wireless communication, broadband
wireless secure access, space communication and so on. (1) Terahertz wave is easily absorbed by
moisture in the air when it propagates in the air, which is more suitable for high-speed
short-distance wireless communication; (2) narrower beam, better directivity, stronger
anti-jamming ability, and can achieve secure communication within 2-5 km. (3) Terahertz wave
has high frequency and wide bandwidth, which can meet the requirement of spectrum bandwidth
for wireless broadband transmission. The terahertz wave spectrum ranges from 108 to 1013 GHz,
which has several tens of GHz available spectrum bandwidth and can provide communication rate
over Tb/s. (4) Space communication. In outer space, terahertz wave has relatively transparent
atmospheric windows near 350, 450, 620, 735 and 870 microns. It can transmit without loss and
achieve long-distance communication with very low power. In addition, compared with wireless
optical communication, the beam is wider, the receiver is easy to align, the quantum noise is lower,
and the antenna terminal can be miniaturized and planar. Therefore, terahertz wave can be widely
used in space communication, especially for the width communication between satellites and
between satellites and ground. (5) The terahertz band has short wavelength and is suitable for
Massive MIMO with more antenna arrays (the same size or even smaller antenna volume as
millimeter wave). Preliminary studies show that the beam configuration and spatial multiplexing
gain provided by Massive MIMO can overcome the rain and atmospheric degradation of terahertz
propagation and meet the coverage requirements of dense urban areas (for example, 200 m cell
radius). (6) High energy efficiency. Compared with wireless optical communication, terahertz
wave has low photon energy, about 10-3eV, only 1/40 of visible light. It can be used as an
information carrier to achieve high energy efficiency. (7) Strong penetration. Terahertz wave can
penetrate the material with a small attenuation, which is suitable for the communication needs of
some special scenarios.
Terahertz band has irreplaceable advantages for mobile communication, but it also faces
many challenges: (1) coverage and directional communication. The propagation characteristics of
electromagnetic wave show that the free-space fading is proportional to the square of frequency,
so terahertz has larger free-space fading than low-frequency band. Terahertz propagation
characteristics and huge antenna arrays mean that terahertz communication is highly directional
beam signal propagation. We need to redesign and optimize the relevant mechanisms according to
the signal characteristics of this highly directional propagation. (2) Large-scale fading
characteristics. Terahertz signal is very sensitive to shadows and has a great influence on coverage.
For example, if the signal attenuation of brick is as high as 40-80 dB, the human body can bring
20-35 dB signal attenuation. However, the effect of humidity/rainfall fading on terahertz
communication is relatively small, because the humidity/rainfall fading increases rapidly below
100 GHz with the increase of frequency, but is relatively flat above 100 GHz. Several terahertz
bands with relatively low rain attenuation can be selected as typical bands for future terahertz
communications, such as the near bands of 140 GHz, 220 GHz and 340 GHz [47]. (3) Fast
channel fluctuation and intermittent connection. Given the moving speed, the coherence time of
the channel is linear with the carrier frequency, which means that the coherence time of the
terahertz band is very small and the Doppler spread is large, and the change of the frequency band
is much faster than that of the current cellular system. In addition, higher shadow fading will lead
to more intense fluctuation of terahertz propagation path fading. At the same time, terahertz
system mainly consists of microcells with small coverage and high spatial orientation, which
means that path fading, service beam and cell correlation will change rapidly. From the system
point of view, it means that the connection of terahertz communication system will be highly
intermittent, and a fast adaptive mechanism is needed to overcome this fast changing intermittent
connection problem. (4) Processing power consumption. A major challenge in utilizing very large
antennas is the power consumption of broadband terahertz system (A/D) conversion. Power
consumption is generally linear with sampling rate, and exponential with sampling number per bit.
Large bandwidth and huge antennas in terahertz band need high resolution quantization. It will be
Yajun ZHAO, et al. 6G Mobile Communication Network: Vision, Challenges and Key Technologies
a great challenge to realize low power and low cost equipment.
In order to support terahertz communication, the following aspects need to be further studied:
(1) semiconductor technology, including RF, analog baseband and digital logic; (2) research on
high-speed baseband signal processing technology with low complexity and low power
consumption and integrated circuit design method to develop terahertz high-speed communication
baseband platform; (3) modulation and demodulation, including terahertz direct modulation and
terahertz mixing. Frequency modulation and terahertz photoelectric modulation; (4) waveform and
channel coding; (5) synchronization mechanism, such as high-speed and high-precision
acquisition and tracking mechanism, hundreds of magnitude antenna array synchronization
mechanism; (6) channel measurement and modeling of terahertz space and ground
communications. In order to balance the performance, complexity and power consumption of
terahertz communication, the above-mentioned technical issues need to be considered
In addition, the ITU has decided to classify 0.12THz and 0.2THz as wireless communications,
but the rules for the monitoring of spectrum above 0.3THz are not clear and have not yet been
unified globally. It needs the joint efforts of ITU and WRC to actively promote consensus.
The research of terahertz communication technology has only been 20 years, many key
devices have not been developed successfully, some key technologies are not mature enough, and
a lot of research work needs to be done. However, terahertz communication is a promising
technology. With the breakthrough of key devices and key technologies, terahertz communication
will bring far-reaching impact on human production and life.
3.1.2 Visible Light Communications
Optical Wireless Communications (OWC), which includes infrared, visible and ultraviolet
bands, is a possible complementary technology to the existing radio frequency communication
technology. It can effectively alleviate the current radio frequency band tension. Among them, the
visible band is the most important band of OWC, which will be discussed in this section.
OWC system in visible band (390-700 nanometers) is usually called Visible Light
Communications (VLC), which makes full use of the advantages of visible light emitting diodes
(LED) to achieve dual purposes of lighting and high-speed data communication. Compared with
radio communication, VLC has many attractive advantages. Firstly, visible communication
technology can provide a large number of potentially available spectrum (THz bandwidth), and
spectrum use is unlimited, without the authorization of spectrum regulators. Secondly, visible light
communication does not produce electromagnetic radiation, nor is it susceptible to external
electromagnetic interference, so it can be widely used in special occasions, such as hospitals,
aircraft, gas stations and chemical plants, which are sensitive to electromagnetic interference and
even have to eliminate electromagnetic interference. Thirdly, the network security of visible light
communication technology is higher. The transmission medium used in this technology is visible
light, which can not penetrate the wall and other occlusions, and the transmission is limited to the
user's visual range. This means that the transmission of network information is limited to a
building, which effectively avoids the malicious interception of transmission information from
outside and ensures the security of information. Finally, visible light communication technology
supports the rapid construction of wireless networks, which can facilitate the flexible
establishment of temporary networks and communication links, and reduce the cost of network
use and maintenance. Radio frequency signals, such as metro and tunnel, cover blind areas. If
radio frequency communication is used, it will require high cost to establish base stations and pay
high maintenance costs. The indoor visible light communication technology can use its indoor
lighting source as the base station, combined with other wireless/wired communication technology,
to provide users with convenient indoor wireless communication services.
Typical application scenarios of OWC include: optical hotspots (especially indoor scenarios),
short distance communication, intersatellite link laser communication and submarine
communication (to overcome attenuation and electromagnetic interference). The OWC technology
of these typical application scenarios deserves further study and targeted optimization.
3.2 Fundamental Technologies
There are many potential basic technologies that constitute 6G system. This chapter will
discuss the most potential key basic technologies, including sparse theory (mainly referring to
compressed sensing), new channel coding, very large-scale antenna, flexible spectrum technology.
3.2.1 Sparse Theory-Compressed Sensing
Signal sampling is a bridge between analog sources and digital information. The huge
demand for information brings tremendous pressure on signal sampling, transmission and storage.
How to relieve this pressure and extract useful information effectively is one of the key problems
in signal and information processing. Traditional signal processing is based on Shannon-Nyquist
sampling theorem. Signals are usually sampled and compressed, and must be sampled and
processed at a rate higher than Shannon-Nyquist frequency. Unlike Shannon-Nyquist signal
sampling mechanism, Donoho [48] and Candidates, Tao and Romberg [49] have proposed a novel
sampling theory called Compressed Sensing/Compressive Sampling (CS) based on signal sparsity
in recent years, which successfully implements simultaneous sampling and compression of signals
and provides a solution to alleviate the above pressure. CS is an attractive example of acquiring,
processing and restoring sparse signals. This new mode is a competitive alternative to traditional
information processing operations (including sampling, sensing, compression, estimation and
detection). This research idea challenges the theoretical limit of Shannon-Nyquist sampling
theorem [49], and has an extremely important impact on the whole field of signal processing.
CS theory is one of the research hotspots in the field of signal processing [48]-[49] [51]-[57].
The core of CS is to recover sparse signals from under-determined linear systems in a
computationally efficient way, that is, a small amount of linear measurement (projection) of
signals contains sufficient information for their reconstruction. Compressed sensing theory points
out that when the signal is sparse or compressible in a transform domain, the transformation
coefficient linear projection can be used as a low-dimensional observation vector by using the
measurement matrix incoherent with the transform matrix. At the same time, the projection
preserves the information needed to reconstruct the signal. By further solving the sparse
optimization problem, it is possible to accurately or highly probabilistic from the low-dimensional
observation vector. Reconstruct the original high-dimensional signal. In this theoretical framework,
the sampling rate no longer depends on the bandwidth of the signal, but largely depends on two
basic criteria: sparsity and incoherence, or sparsity and equidistant constraints. In compressed
sensing theory, the signal sampling is replaced by information sampling (i.e. data observation or
sensing) at the originator, while signal reconstruction at the receiver replaces traditional decoding,
Yajun ZHAO, et al. 6G Mobile Communication Network: Vision, Challenges and Key Technologies
so it is not limited by Shannon-Nyquist sampling rate. This advantage makes compressed sensing
have great application prospects in many aspects of communication and information processing.
The problems of the traditional Shannon-Nyquist sampling theorem are as follows: for
high-bandwidth signals, Shannon-Nyquist sampling theorem requires at least twice the sampling
rate of bandwidth, and requires high sampling hardware equipment; at the same time, a large
number of signal sampling points generated bring heavy burden on subsequent transmission and
storage, which not only wastes a lot of communication bandwidth resources, but also increases the
cost of communication equipment. In addition, because of the large amount of data to be
processed, the real-time performance of the system for signal processing will be reduced. Based
on the CS characteristics mentioned above, the problem of Shannon-Nyquist sampling theorem
can be overcome by using CS characteristics, and the performance of future communication
systems can be improved better: the transmission capacity of useful information can be greatly
improved, and the transmission and processing delay of useful information can be reduced. In
recent years, various wireless communication applications utilizing sparsity of target signals have
been proposed. Notable examples include channel estimation, interference cancellation, direction
estimation, spectrum sensing and symbol detection [52].
Compressed sensing/sparse theory has been used in a few applications in 5G, such as Sparse
Code Multiple Access (SCMA) and Massive MIMO channel estimation. However, due to the
contradiction between the lack of technical maturity and the urgency of standardization time, it
was not adopted in 5G standard. Faced with the challenge of 6G in the future, the application of
compressed sensing theory in 6G has greater urgency: the next generation of wireless transmission
is faced with ultra-large bandwidth, ultra-large antenna and ultra-dense base stations, which will
require incalculable computational complexity, hardware cost and energy consumption; massive
Internet of Things (IOT) nodes/tactile nodes also need to use compressed sensing theory to solve
the problem of signal acquisition and compression [51]. Based on the current development trend
of compressed sensing/sparse theory, 10 years later, its technology maturity can fully meet the
needs of Engineering applications, thus engineering landing in 6G system becomes possible.
Considering the requirements and challenges that 6G will face, there are three typical
application scenarios of compressed sensing: UWB spectrum sensing, wireless sensor network
(wireless tactile network), and ultra-large antenna.
3.2.2 New Channel Coding
Channel coding is the basis of wireless communication. Next generation channel coding
mechanism needs to be studied and broken through first, which will lay the foundation for future
6G wireless communication system.
Compared with the current 5G system, the next generation channel coding mechanism
research needs to meet the new and more complex heterogeneous wireless communication needs
scenarios and business needs in the future. Several typical scenarios need to be considered:
ultra-high throughput (Tb/s level), ultra-wide bandwidth channel, ultra-high frequency channel,
visible light channel, high altitude/space channel, ocean/deep sea channel, deep earth channel and
other complex propagation environments and more heterogeneous and diverse business types.
The application of channel coding in future wireless communication systems involves
advanced channel coding algorithms, powerful chips and implementation technologies. The
former is constrained by the realization of the latter project, so a comprehensive study and
breakthrough are needed. Channel coding mechanism can be based on the existing advanced
coding mechanisms (such as Turbo, LDPC, Polar, etc.) to obtain the basic channel coding
principles suitable for future communication system application scenarios, and further study the
new coding and decoding mechanism and the corresponding chip implementation scheme. It is
necessary to select the relevant channel coding mechanism currently being studied by academia,
considering its theoretical performance cap and corresponding engineering implementation
constraints, as a candidate breakthrough direction of channel coding mechanism for next
generation wireless communication systems. The application of AI in wireless communication
also provides a new paradigm for channel coding research. Classical error-correcting codes are
designed according to coding theory, while AI-driven methods no longer need to rely on coding
theory, which provides a possibility to design a new channel coding mechanism to break through
existing theories[58].
In addition, the channel coding design used in existing projects is assumed to be a
point-to-point Gauss channel, while the actual communication is an interference/fading channel in
a multi-user complex network scenario, so the existing channel coding mechanism is suboptimal
for the actual interference channel. In the future, the interference relationship of communication
networks will be more complex, so it is necessary to consider the optimal design based on the
assumption of interference channel, for example, multi-user channel coding.
3.2.3 Very Large Scale Antenna
Multi-antenna technology, especially very large-scale antenna technology, is one of the key
technologies to improve the spectrum efficiency of wireless mobile communication systems. If we
want to make better use of multi-antenna gain in the future 6G network, we will have to face many
unprecedented demands and challenges.
From the perspective of candidate spectrum, terahertz spectrum communication is very
possible for 6G. At present, the characteristics of terahertz spectrum have not been fully studied.
How to use large-scale antenna in terahertz spectrum is faced with many difficulties, including
breakthroughs in engineering theory and design and implementation. At the same time, the
introduction of terahertz spectrum also means that the spectrum range of future communication
systems will be wider, including low frequency below 6GHz, millimeter wave above 6GHz and
higher frequency terahertz. In addition, the number of large-scale antenna arrays in terahertz
spectrum will be greatly increased, which requires higher spectral efficiency.
Faced with the challenge of 6G requirement, large-scale antenna technology needs to study
and break through the following problems: solving the problems of theory and technology
realization in the field of cross-band, high efficiency, all-space coverage antenna; researching
configurable, large-scale array antenna and radio frequency technology, breaking through the
multi-band and high-integrated radio frequency circuit, including low power consumption, high
efficiency, low noise and non-linearity. The key challenges include the design theory and
technology of new large-scale array antenna, the theory and implementation method of high
integration RF circuit optimization design, and the design technology of high performance
large-scale analog beam forming network.
In addition, in order to obtain large-scale antenna gain, channel status information (CSI) is
needed at both transmitter and receiver. Even assuming TDD duplex mode, there will still be pilot
pollution problem, that is, the upstream link pilot sequences from different cells interfere with
Yajun ZHAO, et al. 6G Mobile Communication Network: Vision, Challenges and Key Technologies
each other. These problems are very challenging for very large antennas, even if only to obtain
imperfect CSI. Especially for large-scale antennas with terahertz spectrum, the number of arrays is
more, and the number of channels to be estimated will be very large. The design of reference
signal, channel estimation and feedback for terahertz spectrum antenna based on compressed
sensing theory is a good choice, including FDD and TDD duplex Massive MIMO scenarios
[59]-[61]. In Massive MIMO system [62]-[63], transmitters and/or receivers are equipped with
large-scale antenna arrays. Due to the limited number of scattering groups and the improved
spatial resolution, the channel can be sparsely represented in the angular domain [64]-[66]. In
addition, relevant research and practical measurements show that terahertz signal arrival consists
of a small number of path clusters, and each cluster has only a small angle expansion. These
terahertz spectra and their significant sparse characteristics of large-scale antennas are conducive
to the use of compressed sensing technology, which can effectively reduce processing complexity
and improve system performance.
3.2.4 Flexible Spectrum
Several potential key fundamental technologies discussed above are aimed at further
improving spectral efficiency so that spectral efficiency approaches the upper limit of channel
capacity and achieves peak network rate under ideal assumptions. In the actual network, the more
typical situation is the unbalance of spectrum demand, including the unbalance between different
networks, the unbalance between different nodes in the same network, the unbalance between the
transceiver links of the same node, and so on. These unbalanced characteristics lead to the low
utilization of spectrum. This chapter will discuss two potential candidate technologies to solve the
above-mentioned unbalanced spectrum requirements: (1) spectrum sharing, mainly used to solve
the unbalanced spectrum requirements between different networks; (2) full-degree-of-freedom
duplex, mainly used to solve the unbalanced spectrum requirements between different nodes in the
same network and between the transceiver and receiver links of the same node. The external
contradiction between the surge of wireless communication traffic demand and the shortage of
spectrum resources is driving the internal change of wireless communication standards. To further
improve the spectrum efficiency and eliminate the limitations on the utilization of spectrum
resources has become a goal of future wireless communication. Spectrum Sharing
In order to meet the demand of spectrum resource utilization in future 6G system, on the one
hand, it is necessary to expand the available spectrum, such as terahertz spectrum and visible
spectrum, as described in Section 3.1; on the other hand, it is necessary to change the spectrum
usage rules, break through the current situation of authorized carrier usage, allocate and use
spectrum in a more flexible way, so as to improve the utilization rate of spectrum resources. At
present, cellular networks mainly use authorized carrier. The owner of spectrum resources has
exclusive spectrum access. Even if the spectrum resources are temporarily idle, other demanders
have no chance to use them. The exclusive authorized spectrum has strict restrictions and
requirements on users'technical indicators and usage areas, which can effectively avoid
inter-system interference and can be used for a long time. However, while this method has high
stability and reliability, there are also some problems such as spectrum idleness and inadequate
utilization caused by the exclusive band of authorized users, which aggravate the contradiction
between spectrum supply and demand. Obviously, breaking the rule of static spectrum division
and using exclusive authorized spectrum, it is better to adopt the way of spectrum resource sharing
Based on the division of spectrum resource authorization, spectrum sharing can be further
divided into two types: unauthorized spectrum, user's use band is unrestricted, each other has the
same right to use but is not protected, need to avoid mutual interference through technical means;
dynamic spectrum sharing, under the premise of ensuring that the main user is not interfered,
through the design of permission (e.g. Provide access time, access location, transmission power,
interference protection and so on. Give secondary users the right to use spectrum. Secondary users
can use database, spectrum sensing, cognitive radio and other technologies to share spectrum with
primary users in different dimensions such as space, time and frequency.
For the unauthorized spectrum, the main unauthorized carrier bands include 2.4 GHz and 5
GHz, which account for a small proportion of the total available spectrum, and the usage rules of
different countries and regions are not uniform. WLAN system is the most commercialized
technology using unauthorized carriers, but its spectrum efficiency is relatively low. The
introduction of LAA (Licensed-Assisted Access) technology into the standard version of 3GPP
LTE Rel-13 sets a precedent for the use of unauthorized carriers in cellular systems. Currently, the
technical characteristics of NR-unlicensed are being discussed in the 3GPP 5G standard, which
will be included in the 5G NR Rel-16 Standard Version (completed and released at the end of
2019), and 5G NR will also be able to use unauthorized carrier communication. As for dynamic
spectrum sharing, although it has been studied for many years, it has not been used in large-scale
commercial networks.
The reason why spectrum sharing technology has not been fully deployed is due to the
constraints of spectrum allocation rules, but more importantly, the limitation of the maturity of
spectrum sharing technology itself. We still need to make some breakthroughs in the research of
spectrum sharing technology, including efficient spectrum sharing technology and efficient
spectrum monitoring technology, in order to improve the utilization of spectrum resources in the
future network by using shared spectrum technology, and at the same time, it can be more
convenient for spectrum monitoring. The technology of spectrum sharing can be divided into three
categories: one is perception, such as Cognitive Radio (CR) [68]; the other is shared database,
such as spectrum pool technology; and the third is the combination of the two technologies.
Furthermore, the combination of AI and spectrum sharing technology can be used to realize
intelligent dynamic spectrum sharing and intelligent and efficient spectrum supervision [69]-[74]. Free Duplex - Full Duplex
As mentioned above, because the arrival of data packets obeys poisson distribution, the
resource utilization of transceiver links (generally referred to as uplink and downlink) in real
networks fluctuates dynamically and is extremely unbalanced. Enhancing the existing duplex
technology is to achieve flexible spectrum allocation between transceiver links (or flexible
spectrum sharing between transceiver links), so as to improve the utilization of spectrum resources
from the duplex dimension.
At present, compared with traditional mobile communication system, 5G system is based on
flexible empty port concept design, while duplex mode adopts dynamic TDD architecture, in
which FDD mode is only a special case of configuration. In addition, 5G and B5G/6G are mainly
Yajun ZHAO, et al. 6G Mobile Communication Network: Vision, Challenges and Key Technologies
available in the frequency band above 2GHz, most of which are TDD spectrum. The CLI-RIM
WID (Cross Link Interference-Remote Interference Management Work Item Description) standard
project to solve downlink/uplink (DL/UL) cross-link interference will be completed in 2019 and
will be included in 5G NR Rel-16 Standard Version [75]. This standard project will introduce two
kinds of interference suppression: the mechanism to solve the problem of cross-link interference
between adjacent base stations and the mechanism to solve the problem of cross-link interference
between remote base stations (cross-link interference caused by atmospheric duct phenomenon).
Once these two types of interference are well addressed, 5G will really be able to support the
commercial deployment of Flexible Duplex features and gradually get rid of the resource
utilization constraints of Fixed Duplex (FDD/TDD). Although the initial technical discussion of
5G involves full duplex technology, it has not been adopted in Chance 5G because of its immature
theoretical and technical research.
With the progress of duplex technology and the maturity of duplex technology in the next
decade, it is expected that the duplex mode in 6G era will realize the real Free Duplex mode. That
is to say, there is no FDD/TDD differentiation anymore, but a flexible and self-adaptive
scheduling mode of flexible duplex or Full Duplex, according to the service requirements between
transceiver and transceiver links. Thus, the limitation of spectrum resource utilization between
transceiver and transceiver links by duplex mechanism is thoroughly broken. Free Duplex mode
can achieve more efficient utilization of spectrum resources by sharing all-degree-of-freedom
(time, frequency and space) spectrum resources between transceiver and receiver links (or DL and
UL), so as to improve throughput and reduce transmission delay. To achieve Free Duplex mode,
the key technical challenge is to break through full-duplex technology. The following figure (Fig.
5) depicts the evolution of duplex mode in wireless mobile communication system.
Figure 5 Duplex Evolution Route of Wireless Mobile Communication System
Full duplex can maximize the freedom of network and access device transceiver design,
eliminate the limitations of FDD and TDD resources, thereby improving spectrum efficiency and
reducing transmission delay.
Improve spectrum efficiency: full-duplex technology based on self-interference
suppression technology can eliminate the limitation of FDD and TDD resource
utilization, and theoretically double the spectrum efficiency.
Reduce transmission delay: the future carrier property should be based on TDD carrier.
DL/UL is scheduled by TDD mode. Even if DL/UL can be dynamically scheduled as
downlink or downlink with flexible slot structure, there will still be some problems,
such as switching delay between downlink and downlink. Full-duplex or partial
full-duplex can overcome the delay, and provide more freedom and flexibility for
DL/UL resource scheduling.
The communication theory and engineering technology involved in full duplex have been
studied for many years, forming a joint self-interference suppression technology route in
propagation domain, analog domain and digital domain. In recent years, many research institutes
have successfully designed full duplex transceiver [76]-[77], and achieved 110dB self-interference
suppression ability [76]. Full duplex communication has a wide range of applications, including
cognitive radio system [78], relay network [79]-[80], bidirectional communication system [81],
device to device (D2D) [82], cellular network [83]-[85]. Among them, more and more attention
has been paid to the application of cellular network, especially in the dense cellular network
scenarios with small coverage and low transmission power.
Based on the technical characteristics of self-interference limitation, full duplex technology is
mainly suitable for the following typical application scenarios: (1) low transmission power
scenarios, including short-range wireless links (e.g. D2D (Device to Device), V2X (Vehicle to
Everything) and small cell (Small Cell) with low transmission power. (2) scenarios equipped
transceiver devices with unlimited complexity and cost, such as wireless Relay and Wireless
Backhaul; (3) scenarios with narrow beams and more spatial freedom, including communication
scenarios using Massive MIMO in the frequency bands of below 6GHz and high frequency bands
of millimeter/terahertz.
In the process of practicalization of full duplex technology, the problems and technical
challenges to be solved include: suppression of high power dynamic self-interference signal,
miniaturization of self-interference suppression circuit in multi-antenna RF domain, new network
architecture and interference elimination mechanism under full duplex system, coexistence and
evolution strategy with FDD/TDD. In addition, from the perspective of engineering deployment, it
is a more important topic to study fully duplex networking technology.
3.2.5 AI-based Wireless Communication
In recent years, with the advent of the era of big data and the growth of a variety of software
and hardware computing resources, artificial intelligence (AI), especially deep learning, has
become a field with many practical applications and active research topics. With the help of deep
learning, through in-depth induction and analysis of data, new and regular information and
knowledge can be obtained, and the model used to support decision-making can be established by
using these knowledge to carry out risk analysis or prediction. The emergence of deep learning has
promoted the rapid development of many fields, such as speech recognition, computer vision,
machine translation and bioinformatics. And academia and industry are constantly thinking about
how to integrate AI into wireless communication systems to achieve a significant improvement in
the efficiency of wireless communication systems [86]-[87]. Existing research has focused on
application layer and network layer. The main idea is to introduce AI, especially deep learning,
into the field of wireless resource management and allocation. However, the research in this
direction is advancing toward the MAC layer and the physical layer, especially in the physical
layer, there is a trend of combining wireless transmission with deep learning. Although large
wireless data makes it possible to combine AI with wireless communication, the research is still in
the preliminary stage of exploration. The development of intelligent communication system needs
a long process, and opportunities coexist with challenges [88].
AI has two main applications in the application layer and network layer of wireless
communication network. First, they can be used for prediction, reasoning and large data analysis.
In this application area, AI functions are related to the ability of wireless networks to learn from
data sets generated by their users, environments and network devices. For example, AI can be used
to analyze and predict the availability status and content requests of wireless users, so that the base
Yajun ZHAO, et al. 6G Mobile Communication Network: Vision, Challenges and Key Technologies
station can determine the user's associated content in advance and cache it, thereby reducing the
data traffic load. Here, user-related behavior patterns (such as mobility and content requests) will
significantly affect what content is cached, which nodes in the network, and when to cache what
content. Secondly, another key application of AI in wireless networks is to implement
self-organizing network operations by embedding AI functions on network edges and network
element entities such as base stations and end-user devices. This edge intelligence is a key enabler
of self-organizing solutions for resource management, user association, and data uninstallation. In
this case, AI can learn the environment and adopt different solutions with the change of the
environment, which makes it possible for the equipment to make independent decisions, thus
realizing network intelligence[89]. Of course, AI can be used for both prediction and
self-organizing operations in wireless communication networks, because these two functions are
largely interdependent.
AI for physical layer transmission mainly presents two types of deep learning networks, one
based on data-driven and the other based on dual-driven with data and model. The deep learning
network with data-driven regards multiple functional modules of wireless communication system
as an unknown black box which is totally replaced by deep learning network. The network relies
on a large number of training data to complete the training from input to output. While, on the
basis of the original technology of wireless communication system, the deep learning network
based on dual-driven with data and model does not change the model structure of wireless
communication system, and uses the deep learning network to replace module(s) or train related
parameters to improve the performance of module(s) rather than a whole communication system.
The AI-based physical layer transmission means that the underlying signal processing and
communication mechanism may break through the traditional communication theory framework,
and adopt the signal processing and communication mechanism based on AI driver. However,
these two kinds of deep learning networks for physical layer transmission face three problems at
(1) AI algorithm based on deep learning mainly uses a large number of training data offline to
optimize parameters training, and because of the limitation of training data acquisition, it is
generally data under specific channel conditions. This processing mechanism results in the
contradiction between off-line static training of training data in specific channel environment and
diversity and dynamic time-varying of wireless channel.
(2) Current deep learning is mainly for real signals, while the signals of the physical layer of
wireless communication are complex signals. How to construct a complex domain signal detection
neural network to match the characteristics of wireless communication signals needs further
(3) The training samples of AI used in physical layer transmission are mainly generated by
mathematical simulation. The simulation data may ignore the impact of some actual
communication environments. In order to better reflect the actual network environment, it is
necessary to use more complete and actually collected data to train and test the corresponding
network. However, how to effectively obtain enough practical and credible training data is a
problem that have to be solved. For example, the actually collected data is complex and diverse,
and there are a large number of false alarm and false detection data. How to effectively clean up
and classify the data will be a great challenge.
In order to realize the vision of "intelligent connectivity" in 6G era, 6G network will be
presented as a network architecture with "Distributed intelligent wireless computing" [90] and the
underlying communication mechanism based on AI. That is to say, in the 6G era, AI will be fully
integrated into the intelligent 6G network system:
AI will dominate the network end-to-end aspects in the future, including smart core
network and smart edge network, smart phones and smart Internet of things (super Internet of
things) terminals, and smart business applications.
Self-evolution performance, such as availability, modifiability, effectiveness, security
and efficiency; self-evolution quality, such as testability, maintainability, reusability,
scalability, portability and flexibility;
The underlying signal processing and communication mechanism may break through the
traditional classical communication theory framework and adopt AI-driven mechanism in an
all-round way. For example, channel coding and decoding based on deep learning [91],
signal estimation and detection based on deep learning [92], MIMO mechanism based on
deep learning [93] - [95], resource scheduling [96] - [97] and allocation [98] - [99] based on
AI, etc.
Network infrastructure has the ability of self-organization and self-optimization, just
like an independent autonomous system.
With the gradual deepening of the integration of ICT industry chain structure, the
acceleration of network cloud reconstruction and transformation, and the evolution of more new
systems and technologies, telecom operators will face more and more pressure and challenges in
network operation. Intelligent network is the future trend of network development, and the mode
of network operation and maintenance will undergo fundamental changes. The network will
gradually change from the current human-driven mode to the self-driven mode. In the future, the
intelligent network will realize a high degree of autonomy through multi-dimensional data
perception such as network data, business data, user data and so on[100].
3.3 Special Technical Features
In order to achieve the vision and challenges of the above 6G network, at least two potential
key proprietary technical features need to be considered in particular, including space-sea
integrated communications and Wireless Tactile Networks (WTN). As mentioned above, these
proprietary technology features are composed of several key basic technology points to meet the
needs of future 6G typical scenarios, and these proprietary technology features are combined to
build an organic 6G system. This chapter will analyze and discuss these two typical proprietary
technical characteristics in detail.
3.3.1 Space-Air-Ground-Sea Integrated Communication
The goal of space-ground-sea integrated communication is to extend the coverage and depth
of communication, that is, to integrate satellite communication (non-terrace communication) and
deep-sea communication (undersea communication) on the basis of traditional cellular network.
The space-air-ground-sea integrated network is based on the ground network and extended by the
space network and undersea network. It covers the natural space such as space, air, land and ocean.
It is the infrastructure for providing information assurance for various user who may access to
subnetwoks of space-based subnetwork (satellite communication network), air-based subnetwork
(aircraft, hot air balloon, unmanned aerial vehicle and other communication network), land-based
Yajun ZHAO, et al. 6G Mobile Communication Network: Vision, Challenges and Key Technologies
subnetwork (ground cellular network), sea-based subnetwork (undersea wireless communication +
coastal wireless network + ocean-going vessel/levitation and islands network, etc.). From the basic
composition, the space-air-ground-sea integrated communication system can include two
subsystems: the Space-ground integrated subsystem combined with terrace mobile communication
network and satellite communication network, and the deep-sea (undersea) communication
subsystem combined with terrace mobile communication network and deep-sea/ocean
communication network. This chapter will discuss the Space-ground integrated communication
and undersea wireless communication. Among them, whether the undersea wireless
communication used to satisfy the deep-sea/ocean communication scenario can become an
integral part of the future 6G network is controversial. This paper is just a throwing brick to attract
jade, trying to put forward as a discussion. Space and Ground Integrated Communication
The Space-ground integrated information network is interconnected by satellite
communication system (space-based backbone network, space-based access network,
ground-based node network) with the ground Internet and mobile communication network to build
a "global coverage, access on demand, secure and credible" Space-ground integrated
communication network system. The following figure provides a reference example of an
integrated Space-ground communication network architecture (Figure 6).
Figure 6 Network architecture for space and ground integrated communication
Literature [101] provides a typical Space-ground integrated communication network
architecture, which can be used as a reference for future research on Space-ground integrated
communication network architecture of 6G network. The author considers that the space-based
backbone network is composed of several backbone satellite nodes in geosynchronous orbit, and
the backbone nodes need broadband access, data relay, routing exchange, information storage,
processing and fusion functions. It consists of a single satellite or multiple satellite clusters. The
space-based access network consists of several access points in high orbit or low orbit to meet the
needs of land, sea and sky. At the same time, the ground-based node network consists of several
ground-based backbone nodes, which mainly complete the functions of network control, resource
management, protocol conversion, information processing, integration and sharing. The network is
formed through the ground high-speed backbone network, and the interconnection and
interoperability with other ground systems are realized.
The Space-ground integrated network, especially the space-based network, is affected by
factors such as the space communication environment and network settings, which are
significantly different from the terrestrial mobile communication network [102]: (1) the space
transmission conditions are limited. Because of the long distance and poor channel quality of
space nodes, links usually have the characteristics of large transmission delay, high interruption
probability and asymmetry; (2) the particularity of space node networking. Spatial node setting is
restricted by orbit and constellation, node height dynamics, sparse distribution, dynamic change of
topological structure, etc. (3) The particularity of system composition and management. There are
a large number of dedicated systems and private networks, which lack unified standards in their
long-term development. The application needs and habits of network management entities are also
quite different. It is difficult for heterogeneous networks in different management domains to
interconnect and cooperate with each other. Because of the significant difference between
space-based network and terrestrial mobile communication network, a large number of mature
technologies in terrestrial mobile communication network can not be directly used in space-based
network. In order to overcome these problems as soon as possible, several aspects should be
considered: network architecture, interface standards, inter-satellite link scheme selection,
space-based information processing, network protocol system, security mechanism, etc.
Five typical application scenarios of future Space-ground integrated communication network
are as follows: (1) all-terrain coverage: areas that can not be covered by ground base stations, such
as oceans, lakes, islands, mountains, etc; mobile platforms, such as aircraft, ocean-going ships,
high-speed rail. (2) Emergency communication: earthquake, tsunami and other disasters. (3)
Broadcasting services: low-speed broadcasting services, such as public security, emergency
response messages, etc; broadcasting, on-demand multimedia services. (4) IoT services: ocean
material tracking, remote equipment monitoring, large-scale equipment information collection; (5)
signaling shunting: the transmission of control surface information through satellite networks.
Based on the current state of development, Space-ground integrated network still needs to be
solved in the following aspects: interconnection and interoperability between traditional satellite
system and mobile communication network, technological breakthrough of satellite
communication system itself, allocation and management of orbital and spectrum resources,
interconnection and interoperability between different satellite systems, etc. Undersea Communication
Undersea wireless communication is the key technology to realize deep-sea ocean
communication. It can be divided into undersea radio electromagnetic wave communication and
undersea non-electromagnetic wave communication (mainly including undersea acoustic
communication and undersea optical communication), which have different characteristics and
application occasions.
Undersea Wireless Electromagnetic Communication
Electromagnetic wave is a shear wave. The penetration depth of a resistive conductor is
directly related to its frequency. The higher the frequency, the greater the attenuation and the
smaller the penetration depth. On the contrary, the lower the frequency, the smaller the attenuation
and the greater the penetration depth. Sea water is a benign conductor with strong skin effect.
Yajun ZHAO, et al. 6G Mobile Communication Network: Vision, Challenges and Key Technologies
Electromagnetic wave transmission in sea water will cause serious impact. Radio electromagnetic
waves, such as short wave, medium wave and microwave, which originally transmit well on land,
can hardly propagate under water due to the severe attenuation. At present, the undersea radio
electromagnetic wave communication developed by various countries mainly uses three low
frequency bands: Very Low Frequency (VLF), Super Low Frequency (SLF) and Extremely Low
Frequency (ELF). Undersea radio and electromagnetic wave communication is mainly used in
undersea communication scenarios of long distance and small depth.
Undersea Acoustic Communication
Undersea acoustic communication is the most mature technology. Sound wave is the main
carrier of undersea information, which has been widely used in undersea communication, sensing,
detection, navigation, positioning and other fields. Sound wave belongs to mechanical wave
(longitudinal wave). The attenuation of signal transmitted undersea is small (its attenuation rate is
one thousandth of electromagnetic wave). It has a long transmission distance and can be used from
hundreds of meters to tens of kilometers. It is suitable for deep water communication with stable
temperature. Undersea acoustic channel is a very complex multi-path transmission channel. It has
high ambient noise, narrow bandwidth, low carrier frequency and large transmission delay. In
order to overcome these disadvantages and improve bandwidth utilization efficiency as much as
possible, new technology schemes need to be further studied, such as multi-carrier modulation
technology, MIMO technology.
Undersea Optical Wireless Communication
Undersea laser communication technology uses laser carrier to transmit information. Because
the attenuation of blue-green laser at 450-530 nm is much smaller than that of other optical bands,
blue-green laser is used as window band in undersea communication. The advantage of blue-green
laser communication is that it has the highest transmission rate in several ways. At ultra-close
range, the rate can reach 100Mbps. Blue-green laser communication has good direction and small
receiving antenna. However, there are still some difficulties in the application of blue-green laser
in short-range communication in shallow water, which need to be further studied and solved. (1)
scattering effect. Suspended particulates and plankton in water have obvious scattering effect on
light. For the short-distance transmission in turbid shallow water, the scattering caused by
undersea particulates is three orders of magnitude stronger than that in air, and the transmittance is
obviously reduced. (2) The absorption effect of optical signal in water is serious. It includes the
absorption of water medium, solute and suspended matter. (3) The interference of background
radiation. At the same time, strong natural light from outside the water surface and radiated light
from undersea organisms will also interfere with the received signal. (4) High precision aiming
and real-time tracking are difficult. There are many activities in shallow water area, so it is very
difficult to keep real-time undersea alignment for mobile receiving and transmitting
communication units. Because laser can only communicate in line of sight, random occlusion
between two communication points will affect communication performance.
3.3.2 Wireless Tactile Network
At present, the IoT network involved in 5G network mainly emphasizes the perception and
connection of all things, and the object connected by 6G network in the future will be universally
intelligent. Its connection and communication relationship is not only perception, but also
real-time control and response, that is, the so-called "Tactile Internet" [103]. "Tactile Internet"
refers to a communication network capable of transmitting control, touch and sensing/driving
information in real time. IEEEP 1918.1 Standard Working Group defines Tactile Internet as a
network or a network for remote access, perception, operation or control of real-time and virtual
objects or processes that perceive real-time. Traditional Internet is only used for the interaction of
information content, while haptic Internet will not only be responsible for the remote transmission
of information content, but also include the remote control and response behavior corresponding
to the transmission of information content. It will provide a true paradigm shift from content
delivery to tele-skill set delivery, which will potentially revolutionize every part of society [104] -
[108]. The three key elements of Tactile Internet are physical real-time interaction (human and
machine access, operate and control objects in a perceptual real-time manner), hyperreal-time
response infrastructure for remote control, and integration of control and communication into a
network application.
We can imagine the future of the world of things-in-things: a large number of things-in-things
devices fill our environment and perform various sensing tasks; these devices can be deployed
randomly, in some organized way (such as roadside sensing), or as part of a common smartphone
platform; then these devices are connected together and communicated through a variety of
complex and incompatible communication protocols. Change data. Some of these devices/nodes
only have simple perception function, others have complex intelligent decision processing
function, and some nodes are responsible for action response. For example, the so-called
"Wireless Cloud" is composed of only perceptive devices. In future wireless networks, a dense
cluster composed of very inexpensive and low-energy wireless perceptive nodes will collaborate
to provide transparent communication services for other terminals. Wireless nodes operate using
the network-aware physical layer, which processes the mixing of overlapping signals they receive
and extracts relevant information from them and forwards it to their destination based on
compressed sensing. Some main application scenarios can include: remote robot control, remote
machine operation, immersive virtual reality, interpersonal tactile communication, real-time tactile
broadcasting, automobile and UAV control, etc. It can be expected that the 6G era is a ubiquitous
"Tactile Internet", which communicates with ubiquitous perceptual objects and/or intelligent
objects to transmit real-time control, touch and sense/drive information, thus realizing the vison of
"Wherever you think, everything follows your heart".
One of the key technological challenges of Tactile Internet is to combine communication,
control and computing systems into a shared infrastructure. The mobile communication system is
integrated into a (bidirectional) real-time control loop by using the mobile communication system
as the underlying wireless network, together with its software and virtualized logical network
element entity, so as to combine the expected real-time control with the efficient computing
capability of network edge [109]. According to ITU-T's technical observation report on haptic
Internet [110], it is necessary to further expand the research in the field of wireless haptic network,
including introducing new ideas and concepts, improving the intrinsic redundancy and diversity of
access network to meet the strict delay and reliability requirements of haptic Internet applications.
The Tactile Internet is still in its infancy. In order to achieve its vision, some open research
challenges need to be addressed. In addition to the physical layer problems such as waveform
selection and robust modulation schemes, the separation/coordination technology between
intelligent control surface and user plane is very important to reduce signaling overhead and air
Yajun ZHAO, et al. 6G Mobile Communication Network: Vision, Challenges and Key Technologies
interface delay. In order to reduce the end-to-end delay, it is necessary to study highly adaptive
network coding technology and scalable routing algorithm. In addition, for haptic Internet
applications, security is one of the most critical requirements. Effective safeguard mechanisms
must be provided to enhance the protection against malicious acts. To ensure that future risks are
avoided, the primary design criteria for WTN should be to assist humans through authorization,
rather than to independently replace humans in the production of new goods and services [111].
In addition, the ubiquitous and densely distributed sensor devices in the future 6G era will
generate a large amount of sensing information, which will pose a huge challenge to the capacity
of wireless networks. In addition, the capacity, cost and energy consumption pressure of sensor
devices for mass information sampling and processing are also huge challenges [112]. To
overcome these challenges of massive information processing, compressed sensing mechanism is
a good choice, that is, WTN is also one of the most typical scenarios used by compressed sensing
mechanism [113]-[115]. The most direct goal of wireless sensor networks is to collect data.
Because the data collected by sensor nodes are sparse and compressible in time-space correlation,
meeting the requirement of signal sparsity and compressibility in the application of compressed
sensing theory, and the resource of sensor nodes is limited, and the performance of sink nodes is
powerful, it is suitable for the characteristics of compressed sensing theory, such as simple coding
and complex decoding. Therefore, the number of wireless sensor networks (WSN) based on
compressed sensing The collected technology has been gradually in-depth and extensive research
and development. WSN based on compressed sensing mechanism has the opportunity to
overcome the problem of traditional signal acquisition and effectively realize the application
requirements of WTN everywhere. In wireless sensor networks, for example, location information
of sensor nodes is needed to perform location awareness, resource allocation and scheduling.
Location information is also an important factor in location-based services. Because there are a lot
of elements in the location grid, this method will produce high computational complexity. Since
the number of target nodes is far less than the number of elements in the grid, the location
information of the target is sparse, so CS technology can be used to locate effectively[116]-[118].
4 Conclusion
In this paper, four key words are used to summarize the future 6G vision: "Intelligent
Connectivity", "Deep Connectivity", "Holographic Connectivity" and "Ubiquitous Connectivity".
These four keywords together constitute the 6G overall vision of "Wherever you think, everything
follows your heart". The technical requirements and challenges faced in realizing the 6G vision
are analyzed, including peak throughput, higher energy efficiency, connection anytime and
anywhere, new theory and technology, and some non-technical factors. Then the potential key
technologies of 6G are classified and discussed: (1) new spectrum communication technology,
including terahertz communication and visible optical communication; (2) fundamental
technology, including sparse theory (compressed sensing), new channel coding, super large-scale
antenna, flexible spectrum use and AI-based wireless communication; (3) special technology
characteristics, including space-air-ground-sea integrated communication and wireless tactile
The 6G vision is exciting, and the key candidate technologies of 6G are full of challenges.
The 6G network will eventually provide terabit rate per second, support an average of 1000 +
wireless nodes per person in 10 years (2030 ~), and provide instant holographic connectivity
anytime and anywhere. The future will be a completely data-driven society in which people and
things are connected universally, almost instantaneously (milliseconds) to form an incredibly fully
connected utopian world.
Acknowledgments In the process of writing this article, we have received great support and help
from Liujun HU, Hongjun LIU, Kaibo TIAN, Xi MENG and so on. Here we express our sincere
thanks! In addition, Qingmei CHEN and others have made important contributions to this article.
Yajun ZHAO, et al. 6G Mobile Communication Network: Vision, Challenges and Key Technologies
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Yajun ZHAO was born in 1976. He
has B.E. and Master degrees. From
2010 to the present time, he has acted
as a radio expert in the wireless
advanced research department in ZTE
Corporation. Before that, he worked
for Huawei on wireless technology
research in wireless research
department. At present, he is mainly engaged in the research of 5G
standardization technology and future mobile communicatio n
technology (6G). His research interests include unlicensed
spectrum, flexible duplex, CoMP and interference mitigation.
algorithm engineer of ZTE Corpor ation, his main research fields
include small cell enhancement, flexible duplex and
communication system operatio n at unlicensed spectrum in
3G/4G/5G system.
Guanghui YU received the
Master and Ph.D. degrees in
automatic control from Beijing
Institute of Technology, Beijing
China, in 1998 and 2003
respectively. Since 2003, he has
acted as a radio expert in the
wireless advanced research
department in ZTE Corporation. His research interests include
Wimax, 2G, 3G, 4G ,5G and B5G/6G design in RAN especially
involved in multiplexing & access, MIMO, interference
management, channel modeling as well as network architecture. He
is also involved as one of the main researchers in the link and
system simulation platform takes part in all kinds of 3GPP
... It is regarded to be a viable technique for future wireless communication that will handle high data speeds [2]. However, as the attenuation of the THz signal, inrease the carrier frequency becomes very serious, it's becomes a very major tricky in THz communications [3]- [4].The hybrid precoding an enormous attraction for the THz-MIMO. The gain of massive MIMO can be appreciated by using the number of radio frequency(RF) chains to improve the high power consumption of RF chains through hybrid precoding [5]- [6]- [7]. ...
... Springer Nature 2021 L A T E X template 4 DPP for THz Massive MIMO in Future Wireless networks ...
Full-text available
Terahertz (THz) communication is developing into an important technology for next 6G networks owing towards the ultra-wide bandwidth it provides. Precoding is a crucial approach in THz communication to get around the THz signals’ severe path loss and support the needed coverage. The primary problems of the prevalent THz precoding approaches for upcoming 6G networks are carefully investigated in this research. To be more precise, we first show how the main distinctions between millimeter-wave and THz channels are made clear. From there, we highlight the main difficulties with THz precoding, including the beam split effect and high power consumption.In THz massive MIMO systems, where the directional beams will split into several substantial directions at different sub-carrier frequencies, recent hybrid precoding approaches relying on frequency-independent phase-shifters are unable to handle the beam split effect. In THz mMIMO systems, the beam split effect will cause a significant array gain loss across the whole bandwidth, which has not been thoroughly studied.As a result, delay-phase precoding and hybrid precoding are suggested in this work. Then, after carefully examining its range of time delayers and antenna elements and making a association with frequency (milli meter wave and SubTHz have been examined), we move on to its design. The suggested delay-phase precoding approaches outperform the other wideband and narrowband precoding techniques already in use. To compare these typical THz precoding techniques and draw some conclusions for their usage in upcoming 6G networks, present simulation results of spectral efficiency.
... Holographic communications and AR, VR, XR will be greatly benefitted by the 6G peak rate as the data rate requirements are very high for these applications as compared with rest of the wireless applications. 40,51,146 c. Increased energy efficiency. ...
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Many scholastic researches have begun around the globe about the competitive technological interventions like 5G communication networks and its challenges. The incipient technology of 6G networks has emerged to facilitate ultrareliable and low‐latency applications for sustainable smart cities which are infeasible with the existing 4G/5G standards. Therefore, the advanced technologies like machine learning (ML), block chain, and Internet of Things (IoT) utilizing 6G network are leveraged to develop cost‐efficient mechanisms to address the issues of excess communication overhead in the present state of the art. Initially, the authors discussed the key vision of 6G communication technologies, its core technologies (such as visible light communication [VLC] and THz), and the existing issues with the existing network generations (such as 5G and 4G). A detailed analysis of benefits, challenges, and applications of blockchain‐enabled IoT devices with application verticals like Smart city, smart factory plus, automation, and XR that form the key highlights for 6G wireless communication network is also presented. In addition, the key applications and latest research of artificial intelligence (AI) in 6G are discussed facilitating the dynamic spectrum allocation mechanism and mobile edge computing. Lastly, an in‐depth study of the existing open issues and challenges in green 6G communication network technology, as well as review of solutions and potential research recommendations are also presented.
... This is the author's version which has not been fully edited and content may change prior to final publication. Approach of 6G Requirements [31], [32] x x x [33][34][35][36] x x x [37][38][39] x x [40][41][42] x x [43][44][45] x x x [46][47][48] x x x x [49], [50] x x x [51][52][53][54] x [55][56][57][58][59][60][61][62][63][64][65][66][67][68][69][70] x [71], [72] x x x x x x [73], [74] x x x x x [75][76][77][78][79][80][81][82][83][84][85][86][87][88][89][90][91][92][93] x x [94][95][96][97][98][99] x x [100], [101] x [103] x x x x [104], [105] x x x x [106], [107] x x [108][109][110] x x x [111], [112] x x x x x [113], [114] x x x [115], [116] x x [117] x ...
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As society evolves as a whole, new demands arise with increasingly demanding prerequisites, consequently requiring more significant effort to be met. Such demands cover emerging applications, such as remote surgeries in Smart Health use cases, whose latency and reliability network requirements cannot be met by current communication systems; or simply improving current applications with more challenging requirements to be achieved, such as increasing the transmission rate in a mobile network, offering Quality of Service (QoS), and consequently, better user experience. Therefore, enabling technologies must be chosen to design an appropriate 6G architecture to address such demands. However, the explosion of emerging applications focused on different scopes and requirements to be met makes choosing these enabling technologies extremely complex and unpredictable. Thus, this article aims to create a methodology for analyzing the relevance of enabling technologies and use it to design an optimal architecture capable of meeting the 6G demands. For this purpose, two methods named as Average (AVG) and Analytic Hierarchy Process (AHP) have been selected, whose objective is to determine the relevance of an enabler for the 6G architecture, taking into account different degrees of influencing variables for this analysis, such as adherence to a certain architectural model; popularity in the research area; degree of innovation; synergy with other enablers; and support for requirements. Each of these methods presents a particular result. In the case of the AVG method, the criteria and variables are evaluated independently, and the arithmetic mean is employed to combine the evaluations into a single measure of suitability. In contrast, the AHP method considers the relative importance of criteria and variables in order to classify an optimal set of enabling technologies capable of fulfilling the key roles to be performed by a 6G architecture, and consequently meeting the main 6G demands. Our evaluation provides a unique perspective on 6G enablers, identifying issues and fostering research for future mobile architectures. The results obtained also provide researchers with the necessary information to stay updated on emerging enabling technologies and their suitability for designing new optimized 6G architectures.
... Nowadays, the internet of things (IoT) has been revolutionizing all aspects of our life, from smart city infrastructures, smart home, ad hoc healthcare and various others. With the advent of the 5G era featuring unprecedented communication speed and capability, a grand vision of the internet of everything has been chased, where several important challenges however remain to be solved such as the lack of spectrum resources, high energy consumption, and high maintenance cost among others [1]. Primarily, reducing the power consumption of powerful IoT devices, especially the communication module, is fundamental. ...
Full-text available
Achieving high-efficient and low-power communication is pivotal yet very challenging in the emerging technologies. Unlike conventional backscatter communication system, we propose and demonstrate an amplitude-reconfigurable metasurface loaded with PIN diodes to build a front-back scattering communication transmitter, which features the exclusive advantages of full-space secondary modulation of the ambient signals with high energy utilization efficiency. Meanwhile, this device can eliminate the interference originated from the ambient source by polarization conversion in the transmission channel. At a modulation rate of 800 kbps and a distance of 80 m, our system can achieve distortion-free transmission of a picture with size of 200 × 200 pixels. In addition, multiple amplitude-shift-keying modulation is also realized by segmenting the metasurface to further increase the communication rate. Due to the advantages of high spectral efficiency and low energy consumption, this system can be widely used in future engineering applications for the internet of things, especially for smart home, agriculture environmental monitoring, wearable sensing and others.
... As 5G technology matures and gradually penetrates the market, people are starting to envision the potential applications of more sophisticated communication systems [1,2]. In order to realize this vision, various wireless communication technologies have been proposed, including terahertz communication [3], air-space-ground integrated networks [4], artificial intelligence (AI)-driven communication [5], inter-protocol communication [6], etc., resulting in a host of new metrics that 6G must satisfy [1,7]. However, the implementation of communication systems based on Shannon's theory of error-correcting information transmission [8] has essentially hit a bottleneck, which may impede classical communication systems from achieving the state-of-the-art (SOTA) metrics proposed for 6G. ...
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Despite the remarkable achievements of modern communication systems based on Shannon’s theory, there is still considerable room for exploration in information transmission capacity, and semantic communication technology has emerged as a promising approach in this regard. Nonetheless, the benefits of semantic communication remain elusive, and the absence of a unified system model has hindered practical implementation. In this context, we contend that semantic communication can benefit from data distortion and the incorporation of natural language modeling information, such that source coding with semantic modeling information does not compromise the performance of semantic communication systems. To fortify our stance, a novel Separated Data-Semantic Coding (SDSC) system is proposed, which disentangles the source coding and semantic coding. Furthermore, relevant experiments are conducted to validate the contention and the SDSC system. By illuminating the superiority of semantic communication, the research not only contributes to the advancement of semantic communication technologies but also facilitates the development of more practical communication systems.
... The core technology for 6G will be THz wave, which has an electromagnetic wave spectrum ranging from 0.1 to 10 THz with a wavelength of 30 to 3,000 microns [69]. The spectrum is in the transition region where macro-electronics and microphotonics collide, especially between microwave (from its lower band) and infrared light (up to its higher band) [70]. Despite the fact that the frequency band (from microwave to optical wave) of THz may not be fully operated, THz communication has abundant resources of the spectrum and an ultra-high transmission rate, which provide precious broadband wireless access for future mobile networks [71]. ...
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Handover (HO) management is essential in any mobile cellular network. It ensures seamless connectivity to the User Equipment (UE) while moving from a Base Station (BS) to another within the coverage area. HO optimization refers to adopting intelligent and automatic HO techniques in mobile networks. HO optimization is taking more importance in the Fifth-Generation (5G) and Beyond (B5G) systems due to the requirements and specifications that B5G targets. The requirements of the B5G, such as global connectivity, ultra-low latency, big data analytics, extreme data rate transmissions, a massive number of devices in a small area, etc., and the new technologies that will support the B5G network, such as Millimeter Wave (mmWave), Terahertz (THz) communication, Ultra-Dense Networks (UDNs), etc. All these cause new HO optimization challenges and require new solutions for HO optimization techniques. This paper comprehensively provides the HO optimization challenges and solutions in B5G. Firstly, it provides a research background and explanation for the HO in legacy. Then, it investigates the HO optimization challenges in B5G, including future research directions. After that, the paper discusses the most prominent and recent techniques and technologies solutions for HO optimization management in B5G. Finally, it highlights the potential techniques for HO optimization in B5G.
Full-text available
Due to the growing need for greater quality of service, data rates, capacity, and decreased latency, cellular communication is evolving. The design of cellular networks is being dramatically enhanced in order to meet these demands. The needs and demands are fulfilled due to new multiple access methods, modulation techniques, emerging technologies, etc. In this paper, a comprehensive study on cellular evolution from the first generation (1G) to sixth generation (6G) is presented. The cellular network designs, multiple access strategies, modulation techniques, and emerging technologies are considered in the study. The architecture of the cellular network is given from 1G to 5G. Some of the most important emerging technologies for improving architecture and meeting user demands are covered. Massive MIMO, software-defined networking, mmWave, and other upcoming technologies are among them. Additionally, several access mechanisms ranging from 1G to 5G are investigated. There is a comparison of several generations of cellular communication. The study also gives a preview of what the upcoming 6G may bring. There are obstacles and issues with 6G that are discussed.
Currently, the Internet of Things (IoT) is a highly effective and realistic wireless communication system concept. In this chapter, we have explored the vision of sixth-generation (6G)- IoT-enabled communication networks for sustainable smart cities, along with their intelligent framework. The proposed framework comprises real-time sensing, computing, and communication systems. Furthermore, we have emphasized the architecture and requirements of the 6G-IoT network to meet the growing demand for a sustainable smart city. Additionally, we describe emerging technologies for 6G, including artificial intelligence/machine learning, spectrum bands, sensing networks, extreme connectivity, new network architectures, security, and trust. These technologies enable the development of 6G-IoT network architectures that ensure the quality of service (QoS)/quality of experience (QoE) necessary to support a massive number of devices. Moreover, we have highlighted potential challenges and research directions for future 6G-IoT wireless communication research in the context of sustainable smart cities.
Mobile communications has never ceased to evolve, and has undergone radical transformation from first generation (1G), featuring analog communication, to fifth generation (5G), realizing the connectivity of everything. Mobile communications has profoundly changed the way people live, becoming an engine for accelerating the digitalization and informatization of the social economy. 5G is already on the fast track to large-scale commercialization. It will provide high-speed, low-latency, and large-capacity connections for Internet of Things (IoT) and usher in a brand-new era of Internet of Everything (IoE), penetrating various industries (such as manufacturing, transportation, and agriculture) and stimulating innovation and development in these industries.
To address the limitations of the current proactive content caching technology for the 6th generation (6G) mobile network, this article comprehensively analyzes the complex application scenarios of proactive content caching technology for wireless edge networks. It constructs an accurate content popularity prediction model, develops a user-device-oriented proactive content caching mechanism, establishes an interpretable cached content replacement strategy, and designs a reliable interdevice content sharing service model to achieve accurate, effective, trustworthy, and practical results. In this article, we analyze the proactive content caching technology for wireless edge networks. Based on the analysis of the core theory and application scenarios of proactive content caching in wireless edge networks, this article focuses on improving the hit rate of content caching in edge devices, improving the quality-of-experience (QoE) of end-users accessing content, enhancing the robustness of proactive content caching schemes, and conducting in-depth research on the key technologies and methods involved. The proposed proactive content caching technology for wireless edge networks is validated and improved through experimental research.
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The evolving Fifth Generation New Radio (5GNR) cellular standardization efforts at the Third Generation Partnership Project (3GPP) brings into focus a number of questions on relevant research problems in physical-layer communications for study by both academia and industry. To address this question, we show that the peak download data rates for both WiFi and cellular systems have been scaling exponentially with time over the last twenty five years. While keeping up with the historic cellular trends will be possible in the near-term with a modest bandwidth and hardware complexity expansion, even a reasonable stretching of this road-map into the far future would require significant bandwidth accretion, perhaps possible at the millimeter wave, sub-millimeter wave, or Terahertz (THz) regimes. The consequent increase in focus on systems at higher carrier frequencies necessitates a paradigm shift from the reuse of over-simplified (yet mathematically elegant) models, often inherited from sub-6 GHz systems, to a more holistic view where real measurements guide, motivate and refine the building of relevant but possibly complicated models, solution space(s), and good solutions. To motivate the need for this shift, we illustrate how the traditional abstraction fails to correctly estimate the delay spread of millimeter wave wireless channels and hand blockage losses at higher carrier frequencies. We conclude this paper with a broad set of implications for future research prospects at the physical-layer including key use-cases, possible research policy initiatives, and structural changes needed in telecommunications departments at universities.
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Activity recognition, as an important component of behavioral monitoring and intervention, has attracted enormous attention, especially in Mobile Cloud Computing (MCC) and Remote Health Monitoring (RHM) paradigms. While recently resource constrained wearable devices have been gaining popularity, their battery life is limited and constrained by the frequent wireless transmission of data to more computationally powerful back-ends. This paper proposes an ultra-low power activity recognition system using a novel adaptive compressed sensing technique that aims to minimize transmission costs. Coarse-grained on-body sensor localization and unsupervised clustering modules are devised to autonomously reconfigure the compressed sensing module for further power saving. We perform a thorough heuristic optimization using Grammatical Evolution (GE) to ensure minimal computation overhead of the proposed methodology. Our evaluation on a real-world dataset and a low power wearable sensing node demonstrates that our approach can reduce the energy consumption of the wireless data transmission up to 81.2% and 61.5%, with up to 60.6% and 35.0% overall power savings in comparison with baseline and a naive state-of-the-art approaches, respectively. These solutions lead to an average activity recognition accuracy of 89.0% only 4.8% less than the baseline accuracy-while having a negligible energy overhead of on-node computation.
Conference Paper
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A major challenge of screen-camera visual multiinput multi-output (MIMO) communications is to increase the achievable throughput by reducing nonlinear channel effects including perspective distortion, ambient lights, and color mixing. To mitigate such nonlinear effects, an existing transmission method uses linear or simple nonlinear equalizations in decoding operations. However, the throughput improvement from the equalization techniques is often limited because the effects are composed of a combination of various nonlinear distortions. In addition to the above issue, the existing studies consider specific environments, such as indoor and static communications, although screen-camera communications can be used for a variety of applications including outdoor and mobile scenarios. In this study, we propose 1) deep neural network (DNN)-based decoding for screen-camera communications to increase the achievable throughput and 2) Unity 3D-based evaluation methodology to synthetically learn the DNN for being robust against many different screen-camera environments. The DNN finds the best nonlinear kernels for equalization from numerously captured images, and then decodes original bits from newly captured images based on the trained nonlinear kernels. In the Unity-based evaluation tool, we can easily capture numerous photo-realistic images in different screen-camera scenarios to learn the impact of perspective distortion, screen-to-camera distance, motion blur, and ambient lights on the throughput since Unity-based environment can freely set programmable screens, cameras, and ambient lights on a 3D space. As an initial proof of concept, we demonstrate that the proposed DNN-based decoder scheme improves the achievable throughput by up to 148% compared to existing methods by equalizing nonlinear effects.
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The next-generation wireless networks are evolv- ing into very complex systems because of the very diversified service requirements, heterogeneity in applications, devices, and networks. The network operators need to make the best use of the available resources, for example, power, spectrum, as well as infrastructures. Traditional networking approaches, i.e., reactive, centrally-managed, one-size-fits-all approaches and conventional data analysis tools that have limited capability (space and time) are not competent anymore and cannot satisfy and serve that future complex networks regarding operation and optimization cost-effectively. A novel paradigm of proactive, self-aware, self- adaptive and predictive networking is much needed. The network operators have access to large amounts of data, especially from the network and the subscribers. Systematic exploitation of the big data dramatically helps in making the system smart, intelli- gent, and facilitates efficient as well as cost-effective operation and optimization. We envision data-driven next-generation wireless networks, where the network operators employ advanced data analytics, machine learning and artificial intelligence. We discuss the data sources and strong drivers for the adoption of the data analytics, and the role of machine learning, artificial intelligence in making the system intelligent regarding being self-aware, self- adaptive, proactive and prescriptive. A set of network design and optimization schemes are presented concerning data analytics. The paper concludes with a discussion of challenges and benefits of adopting big data analytics, machine learning, and artificial intelligence in the next-generation communication systems.
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A method based on compressive sensing theory, for sampling Fourier sparse signals for efficient implementation of analog-to-information converters is proposed. The solution reconstructs Nyquist rate high-resolution signal from Nyquist rat e low-resolution and sub-Nyquist rate high-resolution samples. For implementation, an architecture based on customized reconfigurable successive approximation register analog-to-digital converter is proposed, simulated, and demonstrated. The power consumption with a 90-nm CMOS process is less than 26 μW with 1-Msample/s rate in reconfigurable 3/10-bit mode. The number of floating point operations per second needed for signal recovery is less than 2% required by the compressive sensing algorithms. The functionality of the solution has been verified with an experimental system.
In this paper, we investigate an artificial-intelligence (AI) driven approach to design error correction codes (ECC). Classic error-correction code design based upon coding-theoretic principles typically strives to optimize some performance-related code property such as minimum Hamming distance, decoding threshold, or subchannel reliability ordering. In contrast, AI-driven approaches, such as reinforcement learning (RL) and genetic algorithms, rely primarily on optimization methods to learn the parameters of an optimal code within a certain code family. We employ a constructor-evaluator framework, in which the code constructor can be realized by various AI algorithms and the code evaluator provides code performance metric measurements. The code constructor keeps improving the code construction to maximize code performance that is evaluated by the code evaluator. As examples, we focus on RL and genetic algorithms to construct linear block codes and polar codes. The results show that comparable code performance can be achieved with respect to the existing codes. It is noteworthy that our method can provide superior performances to classic constructions in certain cases (e.g., list decoding for polar codes).
To address the question in the subtitle of this article, we start by discussing earlier mobile communication systems, beginning with the first analog wireless cellular standards, then moving on to second generation (2G) [or Global System for Mobile Communications (GSM)], passing third generation (3G) and fourth generation (4G), and proceeding to fifth generation (5G). First, we present each generation's key achievements in terms of user services, each generation's technologyrelated factors of success (called innovations) as well as its relation to regulation, and each generation's potential deficiencies.
Distributed-compressed sensing (DCS)-based channel estimation of multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing for relay communication is considered in this study. Specifically, the pilot allocation is addressed to optimise the channel estimation performance. All the existing works on DCS-based channel estimation pilot placement discussed on the mean square error (MSE) of the estimation probabilistically based on the mutual coherence. On the contrary, the authors try to address the MSE of the estimation directly and optimise the MSE directly and design a pilot pattern to optimise the performance of the estimation. By taking into account the optimisation approach, two combinatorial stochastic algorithms have been presented. These two algorithms utilise cross entropy approach in sequential and parallel form. Simulation results represent that the DCS-based MIMO relay channel estimation using optimised pilot placements will increase the performance from 3 to 12 dB as compared with the conventional least squares (LS) method. Furthermore, parallelism has demonstrated the performance gain. Moreover, the DCS-based MIMO relay channel estimation shows 35% improvement in spectrum efficiency under the same bit error rate performance over the traditional LS-based channel estimation approach, respectively.