As of today, the fifth generation (5G) mobile communication system has been rolled out in many countries and the number of 5G subscribers already reaches a very large scale. It is time for academia and industry to shift their attention towards the next generation. At this crossroad, an overview of the current state of the art and a vision of future communications are definitely of interest. This article thus aims to provide a comprehensive survey to draw a picture of the sixth generation (6G) system in terms of drivers, use cases, usage scenarios, requirements, key performance indicators (KPIs), architecture, and enabling technologies. First, we attempt to answer the question of "Is there any need for 6G?" by shedding light on its key driving factors, in which we predict the explosive growth of mobile traffic until 2030, and envision potential use cases and usage scenarios. Second, the technical requirements of 6G are discussed and compared with those of 5G with respect to a set of KPIs in a quantitative manner. Third, the state-of-the-art 6G research efforts and activities from representative institutions and countries are summarized, and a tentative roadmap of definition, specification, standardization, and regulation is projected. Then, we identify a dozen of potential technologies and introduce their principles, advantages, challenges, and open research issues. Finally, the conclusions are drawn to paint a picture of "What 6G may look like?". This survey is intended to serve as an enlightening guideline to spur interests and further investigations for subsequent research and development of 6G communications systems.

The Road Towards 6G: A Comprehensive Survey

As of today, the fifth generation (5G) mobile communication system has been rolled out in many countries and the number of 5G subscribers already reaches a very large scale It is time for academia and industry to shift their attention towards the next generation At this crossroad, an overview of the current state of the art and a vision of future communications are definitely of interest This article thus aims to provide a comprehensive survey to draw a picture of the sixth generation (6G) system in terms of drivers, use cases, usage scenarios, requirements, key performance indicators (KPIs), architecture, and enabling technologies First, we attempt to answer the question of “Is there any need for 6G?” by shedding light on its key driving factors, in which we predict the explosive growth of mobile traffic until 2030, and envision potential use cases and usage scenarios Second, the technical requirements of 6G are discussed and compared with those of 5G with respect to a set of KPIs in a quantitative manner Third, the state-of-the-art 6G research efforts and activities from representative institutions and countries are summarized, and a tentative roadmap of definition, specification, standardization, and regulation is projected Then, we identify a dozen of potential technologies and introduce their principles, advantages, challenges, and open research issues Finally, the conclusions are drawn to paint a picture of “What 6G may look like?” This survey is intended to serve as an enlightening guideline to spur interests and further investigations for subsequent research and development of 6G communications systems

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Sixth-generation (6G) is envisioned to be characterized by ubiquitous connectivity, extremely low latency, and enhanced edge intelligence. However, enriching 6G with these features requires addressing new, unique, and complex challenges specifically at the edge of the network. In this article, we propose a wireless digital twin edge network model by integrating digital twin with edge networks to enable new functionalities, such as hyper-connected experience and low-latency edge computing. To efficiently construct and maintain digital twins in the wireless digital twin network, we formulate the edge association problem with respect to the dynamic network states and varying network topology. Furthermore, according to the different running stages, we decompose the problem into two subproblems, including digital twin placement and digital twin migration. Moreover, we develop a deep reinforcement learning (DRL)-based algorithm to find the optimal solution to the digital twin placement problem, and then use transfer learning to solve the digital twin migration problem. Numerical results show that the proposed scheme provides reduced system cost and enhanced convergence rate for dynamic network states.

Adaptive Edge Association for Wireless Digital Twin Networks in 6G

Industrial Internet of Things (IIoT) is an emerging area that fifth-generation (5G) mobile communication system penetrates industrial manufacturing applications. The indoor factory has larger space and there are a lot of metal machine tools distributed in it, which makes its radio propagation characteristics and corresponding channel models significantly different from those of the indoor office and indoor hotspot. To support the design and the evaluation of the IIoT techniques, the 3rd Generation Partnership Project (3GPP) released the first 5G IIoT standard model in October 2019. In this article, we give a detailed explanation of this IIoT model and compare it with other indoor models. First, we introduce the standardization of 3GPP IIoT channel model and its motivation. Second, four IIoT subscenarios, which are classified according to the clutter density and antenna height, are described. Third, the potential frequency bands of 5G IIoT are summarized. Fourth, the models of channel parameters, including the path loss and the line-of-sight (LOS) probability, the root mean-square (RMS) delay spread, and the angular spread, are given. Among them, the models of path loss and LOS probability take the antenna height and clutter density into consideration. The model of RMS delay spread changes from frequency-dependent to volume-dependent in order to catch the size variation of factories. Finally, two newly added key channel characteristics, dual mobility and absolute time of arrival, which help to describe the robot movement and positioning, are also presented.

3GPP Standardized 5G Channel Model for IIoT Scenarios: A Survey

Vehicular intelligence in 6G: Networking, communications, and computing

With the 5th Generation (5G) Mobile network being rolled out gradually in 2019, the research for the next generation mobile network has been started and targeted for 2030. To pave the way for the development of the 6th Generation (6G) mobile network, the vision and requirements should be identified first for the potential key technology identification and comprehensive system design. This article first identifies the vision of the society development towards 2030 and the new application scenarios for mobile communication, and then the key performance requirements are derived from the service and application perspective. Taken into account the convergence of information technology, communication technology and big data technology, a logical mobile network architecture is proposed to resolve the lessons from 5G network design. To compromise among the cost, capability and flexibility of the network, the features of the 6G mobile network are proposed based on the latest progress and applications of the relevant fields, namely, on-demand fulfillment, lite network, soft network, native AI and native security. Ultimately, the intent of this article is to serve as a basis for stimulating more promising research on 6G.

Vision, requirements and network architecture of 6G mobile network beyond 2030

The fast deployment and penetration of 4G has cultivated human behaviors on mobile data consumption, leading to explosive growth in mobile traffic and stimulating new requirements on the capabilities of mobile networks. To meet the requirements of mobile networks toward year 2020, the next generation of mobile networks (termed as IMT-2020, or 5G) is designed to support 100 Mbps-1 Gbps user-experienced data rate, 1 ms radio transmission latency, and 1 million connections per square kilometer. Recalling the vision and requirements of 5G targeting for commercial launch in 2020, this article overviews the key features of 5G and compares with those of 4G, and reports the world first field trials conducted to validate the key performance of 5G radio interface in 3.5 GHz band. The trial results show that a 1 ms transmission latency and 1 Gbps data rate are achievable.

5G features from operation perspective and fundamental performance validation by field trial

Orbital Angular Momentum (OAM) multiplexing at radio has been proven as a potential way of enhancing channel capacity. In this paper, we analyze the spatial propagation characteristic of OAM beams and the channel capacity of different receiving antenna array configurations in OAM multiplexing transmission system. Simulation results reveal that an OAM beam becomes more and more divergent as the transmission distance and OAM mode order increases. Moreover, the capacity with one receiving Uniform Circular Array (UCA) outperforms the capacity with multiple receiving UCAs regardless of transmission distance and Transmit-Receive (TX-RX) lateral displacement distance, which provides a reference for receiving antenna design of OAM multiplexing transmission system. Furthermore, we verify that multiplexing more OAM modes can improve system robustness.

Capacity Analysis of Orbital Angular Momentum Multiplexing Transmission System

Grant-free Non-orthogonal Multiple Access (GF-NOMA) is a promising technology for massive access users and sporadic small-packet transmission for Beyond the 5th Generation mobile communication system(B5G) / the 6th Generation mobile communication system (6G). One of the key aspects in GF-NOMA system is the signature/constellation design. However, due to the channel variation and random activation of users, conventional optimization approaches seem unsuitable for such complex models. In this paper, as an initial attempt, we propose a human intelligence (HI)-guided artificial intelligence (AI)-enhanced signature/constellation design method. By separate design of modulation and power allocation inspired by prior knowledge, the proposed deep neuron network (DNN) for NOMA signature/constellation design not only has smaller size of DNN and less training data, but also has stronger interpret-ability. In the last section, via simulations we demonstrate that in terms of bit error rate, the proposed scheme can achieve significant performance gain over the conventional NOMA schemes.

AI-enhanced constellation design for NOMA system: A model driven method

Three dimensional (3D) Multiple Input and Multiple Output (MIMO) is one of the most promising techniques for the 5th generation (5G) mobile communication system. To support its research, the property of elevation angle in 3D channel model should be accurately modeled. Conventionally, 3D channel is modeled with an assumption that the mean elevation angle of multipaths is coincided with the line-of-sight (LOS) direction. In order to investigate its authenticity and give the reliable 3D channel model, extensive 3D multiple antenna field channel measurements with 100 MHz bandwidth are conducted in three typical scenarios, including outdoor to indoor(O2I), urban microcell (UMi) and urban macrocell (UMa). The statistical characteristics and parameters are extracted and analyzed based on the measurement data. It is found that the assumption holds in the LOS condition. However, for non-line-of-sight (NLOS) condition, a difference exists between the mean elevation angle and the direction connecting transmitter and receiver, which is defined as the elevation angle offset. Then, the eigenvalue distribution and capacity are compared between the reconstructed 3D channels with and without elevation angle offset. Results show that the performance of 3D channel with angle offset fits the measurement data better whereas that without angle offset is underestimated.

Guangyi Liu

Papers

Vision, requirements and network architecture of 6G mobile network beyond 2030

5G features from operation perspective and fundamental performance validation by field trial

Capacity Analysis of Orbital Angular Momentum Multiplexing Transmission System

AI-enhanced constellation design for NOMA system: A model driven method

Propagation characteristics of elevation angles and three dimensional fading channel model with angle offset