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Self-attention reinforcement learning for multi-beam combining in mmW ave 3D-MIMO systems

science China(Information sciences) 2023年第6期66卷 204-221页

作者： Yingzhi HUANG Zhaoyang ZHANG Jingze CHE Zhaohui YANG Qianqian YANG Kai-Kit WONG college of Information science and electronic engineering Zhejiang University Department of electronic and Electrical engineering University College London

Machine learning(ML)has been empowering all aspects of the wireless communication system design, among which, the reinforcement learning(RL)-based approaches have attracted a lot of research attention since they can interact with the environment directly and learn from the collected experiences efficiently. In this paper, we propose a novel and efficient RL-based multi-beam combining scheme for future millimeter-wave(mmWave)three-dimensional(3D)multi-input multi-output(MIMO)communication systems. The proposed scheme does not require perfect channel state information(CSI)or precise user location information which both are generally difficult to obtain in practice, and well addresses the crucial challenge of computational complexity incurred by the extremely huge state and action spaces associated with multiple users, multiple paths, and multiple 3D beams. In particular, a self-attention deep deterministic policy gradient(DDPG)-based beam selection and combination framework is proposed to learn the 3D beamforming pattern without CSI adaptively. We aim to maximize the sum-rate of the mmWave 3D-MIMO system by optimizing the serving beam set and the corresponding combining weights for each user. To this end, the transformer is incorporated into the DDPG to obtain the global information of the input elements and capture the signal directions precisely, which leads to a near-optimal beamformer design. Simulation results verify the superiority of the proposed self-attention DDPG over conventional ML-based beamforming schemes in terms of sum-rate under various scenarios.

关键词： reinforcement learning (RL) deep deterministic policy gradient (DDPG) self-attention pre-coding/combining millimeter-wave (mmWave) multi-input multi-output (MIMO)

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Robust federated learning for edge-intelligent networks

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science China(Information sciences) 2022年第3期65卷 246-254页

作者： Zhihe GAO Xiaoming CHEN Xiaodan SHAO college of Information science and electronic engineering Zhejiang University

The rapid development of machine learning and wireless communication is creating a new paradigm for future networks, namely edge-intelligent networks. Specifically, data generated by terminal devices is processed via machine learning at the edge of wireless networks, but not at the cloud. Owing to the growing concern for privacy information sharing, federated learning, as a new branch of machine learning,is appealing in edge-intelligent networks. For federated learning, the wireless transmission capabilities under practical conditions, e.g., imperfect channel state information(CSI), have a great impact on the accuracy of global aggregation of local model updates. Therefore, it is very important to enhance the robustness of communication for federated learning. In order to realize robust communication in the presence of channel uncertainty, we propose a robust federated learning algorithm for edge-intelligent networks, including device selection, transmit power allocation, and receive beamforming. Simulation results validate the robustness and effectiveness of the proposed robust federated learning algorithm in edge-intelligent networks.

关键词： edge-intelligent network federated learning imperfect CSI robust design

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用于5G多波束MIMO系统的先进低温共烧陶瓷封装的39 GHz双信道收发器芯片组

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engineering 2023年第3期22卷 125-140页

作者：尹宇明 Zhilin Chen 赵晨曦刘辉华吴韵秋 Wen-Yan Yin 康凯 School of electronic science and engineering University of Electronic Science and Technology of ChinaChengdu 611731China college of Information science and electronic engineering Zhejiang UniversityHangzhou 310058China

本文介绍了一种用于5G多输入多输出(MIMO)应用的39 GHz收发器前端芯片组。每个芯片包括两个可变增益的频率转换通道,可以同时支持两个独立波束,芯片还集成了一个本地振荡器链和数字模块,用于多芯片扩展和增益状态控制。为了提高射频性能... 详细信息

本文介绍了一种用于5G多输入多输出(MIMO)应用的39 GHz收发器前端芯片组。每个芯片包括两个可变增益的频率转换通道,可以同时支持两个独立波束,芯片还集成了一个本地振荡器链和数字模块,用于多芯片扩展和增益状态控制。为了提高射频性能,对前端系统的关键模块提出了几种电路级改进技术。此外,开发了一种先进的低温共烧陶瓷工艺来封装39 GHz双通道收发器芯片组,实现了低封装损耗和两个发射(TX)/接收(RX)通道之间的高隔离。进行了芯片级和系统级封装(SIP)测量,以演示收发器芯片组的性能。测量结果表明,TX SIP的最大增益为11 dB,饱和输出功率为10 dBm;RX SIP的最大增益为52 dB,噪声系数为5.4 dB,输出压缩点为7.2 dBm。该收发器的单通道通信链路测试表明,64正交调幅(QAM)调制的误差矢量幅度(EVM)为3.72%,频谱效率为3.25 bit·s^(−1)·Hz^(−1);256-QAM调制在1 m距离上的误差矢量幅度(EVM)为3.76%,频谱效率为3.9 bit·s^(−1)·Hz^(−1)。基于该芯片组,还开发了39 GHz多波束原型,用于执行5G毫米波应用的MIMO操作。单流和双流传输的空中通信链路表明,多波束原型机可以覆盖5~150 m的距离,吞吐量相当。

关键词： 5G Multi-beam Multi-input multi-output Millimeter-wave Transceiver Wireless communication

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Radar emitter signal recognition method based on improved collaborative semi-supervised learning

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Journal of Systems engineering and electronics 2023年第5期34卷 1182-1190页

作者： JIN Tao ZHANG Xindong College of Electronic Science and Engineering Jilin UniversityChangchun 130012China

Rare labeled data are difficult to recognize by using conventional methods in the process of radar emitter recogni-tion.To solve this problem,an optimized cooperative semi-supervised learning radar emitter recognition method based on a small amount of labeled data is developed.First,a small amount of labeled data are randomly sampled by using the bootstrap method,loss functions for three common deep learning net-works are improved,the uniform distribution and cross-entropy function are combined to reduce the overconfidence of softmax classification.Subsequently,the dataset obtained after sam-pling is adopted to train three improved networks so as to build the initial model.In addition,the unlabeled data are preliminarily screened through dynamic time warping(DTW)and then input into the initial model trained previously for judgment.If the judg-ment results of two or more networks are consistent,the unla-beled data are labeled and put into the labeled data set.Lastly,the three network models are input into the labeled dataset for training,and the final model is built.As revealed by the simula-tion results,the semi-supervised learning method adopted in this paper is capable of exploiting a small amount of labeled data and basically achieving the accuracy of labeled data recognition.

关键词： emitter signal identification time series bootstrap semi supervised learning cross entropy function homogeniza-tion dynamic time warping(DTW)

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Multi-feed multi-mode metasurface for independent orbital angular momentum communication in dual polarization

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Frontiers of Information Technology & electronic engineering 2023年第12期24卷 1776-1790页

作者： Lingjun YANG Sheng SUNI Wei E.I.SHA Long LI Jun HU School of electronic science and engineering University of Electronic Science and Technology of ChinaChengdu611731China college of Information science&electronic engineering Zhejiang UniversityHangzhou310027China School of electronic engineering Xidian UniversityXi’an710071China

The wavefront control of spin or orbital angular momentum(OAM)is widely applied in the optical and radio fields.However,most passive metasurfaces provide limited manipulations,such as the spin-locked wavefront,a static OAM combination,or an uncontrollable OAM energy distribution.We propose a reflection-type multi-feed metasurface to independently generate multi-mode OAM beams with dynamically switchable OAM combinations and spin states,while simultaneously,the energy distribution of carrying OAM modes is controllable.Specifically,four elements are proposed to overcome the spin-locked phase limitation by combining propagation and geometric phases.The robustness of these elements is analyzed.By involving the amplitude term and multi-feed technology in the design process,the proposed metasurface can generate OAM beams with a controllable energy distribution over modes and switchable mode combinations.OAM-based radio communication with four independent channels is experimentally demonstrated at 14 GHz by employing a pair of the proposed metasurfaces.The powers of different channels are adjustable by the provided amplitude term,and the maximum crosstalk is−9 dB,proving the effectiveness and practicability of the proposed method.

关键词： Orbital angular momentum(OAM) Geometric phase Multi-feed metasurface Spin-decoupled metasurface Vortex beam communication

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An approach for detecting LDoS attack based on cloud model

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Frontiers of Computer science 2022年第6期16卷 123-134页

作者： Wei SHI Dan TANG Sijia ZHAN Zheng QIN Xiyin WANG college of Computer science and electronic engineering Hunan UniversityChangsha410082China

Cybersecurity has always been the focus of Internet research.An LDoS attack is an intelligent type of DoS attack,which reduces the quality of network service by periodically sending high-speed but short-pulse attack traffic.Because of its concealment and low average rate,the traditional DoS attack detection methods are challenging to be effective.The existing LDoS attack detection methods generally have the problems of high FPR and FNR.A cloud model-based LDoS attack detection method is proposed,and a classifier based on SVM is used to train and classify the feature parameters.The detection method is verified and tested in the NS2 simulation platform and Test-bed network environment.Compared with the existing research results,the proposed method requires fewer samples,and it has lower FPR and FNR.

关键词： cybersecurity LDoS attack cloud model SVM

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Ultralow cross talk arrayed waveguide grating integrated with tunable microring filter array

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Chinese Optics Letters 2024年第3期22卷 50-54页

作者：胡鹤鸣刘世平李天文范永杰陈华方青 college of science Kunming University of Science and TechnologyKunming 650093China College of Electronic Science and Engineering Jilin UniversityJilin 130012China

The silicon-based arrayed waveguide grating(AWG)is widely used due to its compact footprint and its compatibility with the mature CMOS process.However,except for AWGs with ridged waveguides of a few micrometers of cross section,any small process error will cause a large phase deviation in other AWGs,resulting in an increasing cross talk.In this paper,an ultralow cross talk AWG via a tunable microring resonator(MRR)filter is demonstrated on the SOI platform.The measured insertion loss and minimum adjacent cross talk of the designed AWG are approximately 3.2 and-45.1 d B,respectively.Compared with conventional AWG,its cross talk is greatly reduced.

关键词： SOI platform arrayed waveguide grating cross talk microring filter array thermo-optic effect

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Low-cost intelligent reflecting surface aided Terahertz multiuser massive MIMO: design and analysis

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science China(Information sciences) 2021年第10期64卷 73-87页

作者： Guanghua YU Xiaoming CHEN Xiaodan SHAO Caijun ZHONG college of Information science and electronic engineering Zhejiang University

Terahertz(THz) multiuser massive multiple-input multiple-output(MIMO) has been envisioned as a promising technique to support massive connectivity in next-generation wireless networks. However,due to ultra-high frequency band, the path attenuation of THz channels is extremely severe, resulting in limited wireless coverage. In this paper, we propose an intelligent reflecting surface(IRS)-assisted THz multiuser massive MIMO technique to enhance coverage. First, we design an IRS-assisted THz communication framework with a low-cost sub-connected hybrid precoding architecture, including uplink data transmission and downlink data transmission. In particular, precoding errors due to the limitations of physical devices and environments are taken into consideration. Then, we derive the closed-form expressions for uplink and downlink spectral efficiencies, and reveal the impacts of system parameters. Finally, we conduct extensive simulations to verify the effectiveness of the proposed IRS-assisted THz multiuser massive MIMO technique.

关键词： THz communication IRS massive MIMO precoding error coverage enhancement

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Integrated Polarity Optimization of MPRM Circuits Based on Improved Multi-objective Particle Swarm Optimization

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Chinese Journal of electronics 2020年第5期29卷 833-840页

作者： FU Qiang WANG Pengjun TONG Nan WANG Mingbo ZHONG Caiming college of science and Technology Ningbo University Faculty of electronic engineering and Computer science Ningbo University college of Electrical and electronic engineering Wenzhou University

Aiming at the multi-objective polarity design of Mixed-polarity Reed-Muller(MPRM) circuit,such as small area and low power consumption, an integrated polarity optimization scheme based on improved Multi-objective particle swarm optimization(MOPSO) is proposed. In the Improved MOPSO(IMOPSO) algorithm,particles in the external archive can be actively evolved through self-learning operations to find better circuit polarity. The particles in the population achieve selflearning fractals by comparing the differences between their own states and individuals in external archive to enhance the evolutionary level of the population. A multiobjective decision model of area and power consumption is established according to the characteristics of MPRM circuit. The tabular technique and the IMPOPO algorithm are combined to obtain the Pareto optimal polarity set of the MPRM circuit for area and power consumption. The MCNC Benchmark circuit is used to test the performance of the algorithm. The results verify the effectiveness of the proposed algorithm.

关键词： Multi-objective particle swarm optimization (MOPSO) Self-learning fractal MPRM circuits Polarity Area-power trade-off

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Physical layer security for massive access in cellular Internet of Things

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science China(Information sciences) 2020年第2期63卷 104-115页

作者： Qiao QI Xiaoming CHEN Caijun ZHONG Zhaoyang ZHANG college of Information science and electronic engineering Zhejiang University

The upcoming fifth generation(5G) cellular network is required to provide seamless access for a massive number of Internet of Things(IoT) devices over the limited radio spectrum. In the context of massive spectrum sharing among heterogeneous Io T devices, wireless security becomes a critical issue owing to the broadcast nature of wireless channels. According to the characteristics of the cellular IoT network,physical layer security(PHY-security) is a feasible and effective way of realizing secure massive access. This article reviews the security issues in the cellular IoT network with an emphasis on revealing the corresponding challenges and opportunities for the design of secure massive access. Furthermore, we provide a survey on PHY-security techniques to improve the secrecy performance. Especially, we propose a secure massive access framework for the cellular Io T network by exploiting the inherent co-channel interferences. Finally, we discuss several potential research directions to further enhance the security of massive IoT.

关键词： 5G and beyond PHY-security massive access cellular IoT

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