在上一期前沿文献中推荐的几篇文章着重探讨了6G网络的技术前景，以及基础学科的突破对于未来通信系统可能带来的支撑作用。本期推荐中，继续聚焦于5G和6G网络的技术演进，从6G的新技术方向，5G承载网新技术、波束赋形算法，到车联网中的节点信誉管理机制，分别选取了最新的研究文献。
本期选取了4篇文献，讨论的内容包括6G时代面临的机遇和挑战，利用已有PON网络作为5G前传接口进行模拟光纤无线下行链路传输IFoF/mmWave，基于深度学习的mmWave波束选择算法及原型验证，以及5G网络中针对恶意车辆识别的一种高效信誉管理算法，推送给相关领域的科研人员，共同探讨。
Toward the 6G Network Era: Opportunities and Challenges
Ioannis Tomkos, etc.
IT Professional,2020,22(1): 34-38
The next generation of telecommunication networks will integrate the latest developments and emerging advancements in telecommunications connectivity infrastructures. In this article, we discuss the transformation and convergence of the fifth-generation (5G) mobile network and the internet of things technologies, toward the emergence of the smart sixth-generation (6G) networks which will employ AI to optimize and automate their operation.
Analog fiber-wireless downlink transmission of IFoF/mmWave over in-field deployed legacy PON infrastructure for 5G fronthauling
K. Kanta, etc.
IEEE/OSA Journal of Optical Communications and Networking ,2020,12(10): D57 - D65
We present a fixed mobile convergence topology for analog intermediate frequency over fiber (A-IFoF)/millimeter-wave (mmWave) transmission, benefiting from the reuse of the deployed passive optical network (PON) infrastructure, towards future mobile fronthaul architectures. Powerful fully programmable gate array boards located inside the access nodes convert the Ethernet-based traffic to orthogonal frequency-division multiplexing (OFDM)-modulated intermediate frequency (IF) waveforms, supporting the A-IFoF propagation through the optical legacy infrastructure. Coexistence of the 5G traffic with the residential legacy traffic for the field propagation is achieved through utilization of unused C-band channels and wavelength-division multiplexing. To this extent, we experimentally demonstrate the downlink operation of a converged A-IFoF/mmWave link, over Telecom Italia’s legacy infrastructure located at Turin. Four-quadrature amplitude modulation (QAM)-OFDM and 16QAM-OFDM IF signals with∼200MHz∼200MHz and 400 MHz bandwidth [considered within the 3rd Generation Partnership Project (3GPP) New Radio specifications] were generated through a radio frequency system-on-chip platform and optically multiplexed with the legacy fiber-to-the-home services. After propagation to the field, the A-IFoF stream was directly fed to a directional wireless link operating at 60 GHz. Successful PON/over-the-air transmission with error vector magnitude (EVM) values well below the 3GPP (<12.5%<12.5%) requirements for 5G New Radio was demonstrated, with a 10.5% EVM for 16QAM-OFDM modulated with 400 MHz bandwidth.
Deep Learning-Based mmWave Beam Selection for 5G NR/6G With Sub-6 GHz Channel Information: Algorithms and Prototype Validation
Min Soo Sim, etc
IEEE Access, 8: 51634 - 51646
In fifth-generation (5G) communications, millimeter wave (mmWave) is one of the key technologies to increase the data rate. To overcome this technology's poor propagation characteristics, it is necessary to employ a number of antennas and form narrow beams. It becomes crucial then, especially for initial access, to attain fine beam alignment between a next generation NodeB (gNB) and a user equipment (UE). The current 5G New Radio (NR) standard, however, adopts an exhaustive search-based beam sweeping, which causes time overhead of a half frame for initial beam establishment. In this paper, we propose a deep learning-based beam selection, which is compatible with the 5G NR standard. To select a mmWave beam, we exploit sub-6 GHz channel information. We introduce a deep neural network (DNN) structure and explain how we estimate a power delay profile (PDP) of a sub-6 GHz channel, which is used as an input of the DNN. We then validate its performance with real environment-based 3D ray-tracing simulations and over-the-air experiments with a mmWave prototype. Evaluation results confirm that, with support from the sub-6 GHz connection, the proposed beam selection reduces the beam sweeping overhead by up to 79.3 %.
A Reputation Management Scheme for Efficient Malicious Vehicle Identification over 5G Networks
Mohammed S. Hadi, etc.
IEEE Wireless Communications,2020,27(3):46-52
A reputation management scheme plays a critical role for secure communications in vehicular networks. However, due to the limited wireless communication in the past few years, the existing solutions fail to capture the current high-performance network communication provided by the 5G network. As a result, the attributes of security and efficiency can hardly be satisfied at the same time. In this article, we propose IDES, which provides a centralized reputation management scheme to detect malicious nodes in the vehicular network. To discuss the feasibility of our scheme, we design a practical system structure to which our reputation management scheme could be applied and discuss the possible threat modes to our system. With a self-developed event-based emulator, we evaluate the performance of our IDES under malicious attack. Toward defense against the 3 thread mode attack we discuss, we prove that our scheme could take effect much faster, and outperforms the current decentralized trust management schemes.
