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Impact of non-ideal UE hardware on cell-free massive mimo network with centralized operation

Science China(Information Sciences) 2024年第4期67卷 255-271页

作者： Ning LI Pingzhi FAN Institute of Mobile Communications Southwest Jiaotong University

This paper investigates the impact of non-ideal user equipment(UE) hardware on a cell-free(CF) massive mimo(mmimo) network with centralized operation under spatially correlated channels. The minimum mean-squared error(MMSE) estimator can be derived with the help of the generic non-ideal UE hardware model. It is demonstrated that even if the effective signal-to-noise ratio approaches infinity, pilot contamination and imperfect hardware can cause a non-zero estimation error floor. After that, a lower bound is determined for the ergodic uplink capacity of the centralized CF mmimo network under non-ideal UE hardware. Moreover, the optimal receive combining vector is obtained to maximize the uplink spectral efficiency(SE). The maximum ratio(MR) and regularized zero-forcing(RZF) combining schemes are offered as alternatives in light of the computational complexity of the MMSE receiver. Comparing the RZF to the MMSE scheme under different levels of hardware impairments, our findings indicate that the RZF receiver suffers a negligible loss in total SE. For MR combining, a novel closed-form uplink achievable SE expression is obtained based on the MMSE estimator and the use-and-then-forget bounding technique. This expression gives vital insights into the achievable uplink performance with UE hardware impairments. Besides, for various hardware impairment factors, the impact of pilot sequence length on average sum SE is disclosed for different receive combining schemes. To increase the overall SE of the max-min fairness scheme, a heuristic fractional power control scheme with UE hardware impairments is developed, which can essentially avoid sacrificing the SE of other UEs while maximizing the SE of the unluckiest UE in the whole network. Finally,our theoretical performance analysis and power control algorithm are validated by simulation results, and fundamental design guidelines are provided for selecting hardware satisfying the practical UE requirements.

关键词： cell-free massive mimo centralized operation spatially correlated channels hardware impairments channel estimation uplink spectral efficiency optimal receive combining pilot length design fractional power control

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cell-free massive mimo for 6G Wireless Communication Networks

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Journal of Communications and Information Networks 2021年第4期6卷 321-335页

作者： Hengtao He Xianghao Yu Jun Zhang Shenghui Song Khaled B.Letaief Department of ECE Hong Kong University of Science and TechnologyHong Kong 999077China Peng Cheng Laboratory Shenzhen 518000China

The recently commercialized fifth-generation(5G)wireless networks have achieved many improvements,including air interface enhancement,spectrum expansion,and network intensification by several key technologies,such as massive multiple-input multipleoutput(mimo),millimeter-wave communications,and ultra-dense *** the deployment of 5G commercial systems,wireless communications is still facing many challenges to enable connected intelligence and a myriad of applications such as industrial Internet-ofthings,autonomous systems,brain-computer interfaces,digital twin,tactile Internet,***,it is urgent to start research on the sixth-generation(6G)wireless communication *** the candidate technologies for 6G,cell-free massive mimo,which combines the advantages of distributed systems and massive mimo,is a promising solution to enhance the wireless transmission efficiency and provide better *** this paper,we present a comprehensive study on cell-free massive mimo for 6G wireless communication networks with a special focus on the signal processing ***,we introduce enabling physical layer technologies for cell-free massive mimo,such as user association,pilot assignment,transmitter,and receiver design,as well as power control and ***,some current and future research problems are described.

关键词： 6G network cell-free massive mimo distributed antenna systems massive mimo user-centric

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Power Optimization in cell-free massive mimo with Non-ideal Hardware Transceiver

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Chinese Journal of Electronics 2020年第1期29卷 190-198页

作者： ZHANG Yao CAO Haotong ZHOU Meng LI Long YANG Longxiang Wireless Communications Key Laboratory of Jiangsu Province Nanjing University of Posts and Telecommunications Department of Information Technology Party School of the Communist Party of China Shandong Provincial Committee

A downlink cell-free massive Multipleinput multiple-output(mmimo) system is explored. To investigate the impact of hardware distortion on downlink cell-free mmimo, this paper recalls a well-established model of hardware impairment and derives a new closedform downlink per-user Spectral efficiency(SE) expression for distributed conjugate beamforming precoding. Based on this trackable expression, two power control algorithms,namely max-total-SE and mixed Quality-of-service(QoS)algorithms, are proposed. Numerical results indicate that the downlink per-user SE is primarily limited by the hardware quality of the receiver, especially when the user corresponds to the receiver. In addition, the proposed max-total-SE algorithm has a fast convergence rate and can significantly improve the total SE compared to the Equal power control(EPC) scheme. What’s more, our mixed QoS algorithm also performs well in many respects.

关键词： cell-free massive mimo Conjugate beamforming Non-ideal hardware transceiver Spectral efficiency QoS constraint

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Joint optimization of spectral efficiency for cell-free massive mimo with network-assisted full duplexing

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Science China(Information Sciences) 2021年第8期64卷 156-171页

作者： Xinjiang XIA Pengcheng ZHU Jiamin LI Hao WU Dongming WANG Yuanxue XIN National Mobile Communications Research Laboratory Southeast University State Key Laboratory of Mobile Network and Mobile Multimedia Technology Zhongxing Telecommunication Equipment Corporation College of Internet of Things Engineering Hohai University

In this paper, we investigate duplex mode selection and transceiver design for cell-free massive multiple-input multiple-output(mimo) with network-assisted full duplexing(NAFD), where the remote antenna units(RAUs) simultaneously serve both uplink and downlink users on the same time-frequency resource, and the joint transmission and reception are done at the central processing unit. We consider that each antenna can operate in three modes, i.e., uplink reception, downlink transmission and sleep. In particular, we model the problem as a mixed-integer optimization problem to maximize the aggregated spectral efficiency(SE) of downlinks and uplinks, where the quality-of-service constraints and power budget constraints are considered. Since the uplinks and downlinks are highly coupled, to address the design problem,we resolve the combinatorial problem by a series of nonconvex-convex approximate methods, such as equivalent formulations, iterative success convex approximations, and binary relaxations. In particular, a two-stage strategy is proposed to solve the optimization problem. In the first stage, we fix the mode selection vectors and then obtain the optimal transceivers with such a fairness strategy. In the second stage, with the transceiver parameters obtained from the first stage, we further optimize the duplex mode of each *** algorithms of the two stages will alternately run in several loops until convergence. Numerical results indicate that the proposed solution can obtain SE performance that is close to the optimal exhaustive search solution and yields a higher SE gain compared with the traditional fixed-mode duplex scheme.

关键词： cell-free massive mimo network-assisted full duplexing mode selection success convex approximations spectral efficiency

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Joint Flexible Duplexing and Power Allocation with Deep Reinforcement Learning in cell-free massive mimo System

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China Communications 2023年第4期20卷 73-85页

作者： Danhao Deng Chaowei Wang Zhi Zhang Lihua Li Weidong Wang School of Electronic Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China School of Information and Communication Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China Key Laboratory of Universal Wireless Communications Ministry of EducationBeijing University of Posts and TelecommunicationsBeijing 100876China

Network-assisted full duplex(NAFD)cellfree(CF)massive mimo has drawn increasing attention in 6G *** this paper,we build an NAFD CF system in which the users and access points(APs)can flexibly select their duplex modes to increase the link spectral *** we formulate a joint flexible duplexing and power allocation problem to balance the user fairness and system spectral *** further transform the problem into a probability optimization to accommodate the shortterm *** contrast with the instant performance optimization,the probability optimization belongs to a sequential decision making problem,and thus we reformulate it as a Markov Decision Process(MDP).We utilizes deep reinforcement learning(DRL)algorithm to search the solution from a large state-action space,and propose an asynchronous advantage actor-critic(A3C)-based scheme to reduce the chance of converging to the suboptimal *** results demonstrate that the A3C-based scheme is superior to the baseline schemes in term of the complexity,accumulated log spectral efficiency,and stability.

关键词： cell-free massive mimo flexible duplexing sum fair spectral efficiency deep reinforcement learning asynchronous advantage actor-critic

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Spectral Efficiency of Superimposed Pilots in cell-free massive mimo Systems with Hardware Impairments

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China Communications 2021年第6期18卷 146-161页

作者： Yao Zhang Meng Zhou Haitao Zhao Longxiang Yang Hongbo Zhu The Department of Wireless Communication Key Lab of Jiangsu Province Nanjing University of Posts and TelecommunicationsNanjing 210003China

In this paper,the spectral efficiency(SE)of an uplink hardware-constrained cell-free massive multi-input multi-output(mimo)system with maximal ratio combining(MRC)receiver filters in the context of superimposed pilots(SPs)is *** closed-form SE expressions for the considered system are derived,which share us with opportunities to explore the impacts of the hardware quality coefficient,the length of coherence interval,and the power balance factor between pilot and data *** results indicate that the achievable SE deteriorates as the hardware quality decreases and is more susceptible to the hardware impairments at the user equipments(UEs).Besides,we observe that SPs outperform regular pilots(RPs)in terms of SE and this performance gain is heavily dependent on the values of power balance factor and coherence ***,the superiorities of SPs over RPs have vanished when severe hardware imperfections are considered.

关键词： cell-free massive mimo hardware impairments superimposed pilots spectral efficiency

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Joint optimization of spectral efficiency and energy efficiency with low-precision ADCs in cell-free massive mimo systems

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Science China(Information Sciences) 2022年第5期65卷 169-183页

作者： Han WANG Chang SUN Jiamin LI Pengcheng ZHU Dongming WANG Xiaohu YOU National Mobile Communications Research Laboratory Southeast University Purple Mountain Laboratories

In cell-free massive multiple-input multiple-output(mimo) systems, it is beneficial to apply low-precision analog-to-digital converters(ADCs) to reduce power consumption, hardware cost, and the load on backhaul link. However, low-precision ADCs will result in serious degradation in spectral efficiency(SE). It is important to achieve a good tradeoff between SE and energy efficiency(EE) for cell-free massive mimo systems with low-precision ADCs. In this paper, we first derive the closed-form expressions of uplink achievable rates with maximal ratio combining(MRC) receiver and zero-forcing(ZF) receiver in cell-free massive mimo systems. Then we analyze the EE model of cell-free massive mimo systems. Based on the above analysis, the tradeoff between SE and EE is studied. Moreover, we propose two quantization bit allocation algorithms to optimize the SE and EE jointly from the perspective of multi-objective *** algorithm is based on the deep Q-network(DQN) and the other one is based on the non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ). The proposed algorithms provide more feasible solutions and achieve better system performance than equal quantization bit allocation algorithm. Numerical results verify the accuracy of the derived closed-form expressions and the effectiveness of the proposed optimization algorithms.

关键词： cell-free massive mimo low-precision ADC spectral efficiency energy efficiency multi-objective optimization

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Wireless Powered IoE for 6G: massive Access Meets Scalable cell-free massive mimo

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China Communications 2020年第12期17卷 92-109页

作者： Shuaifei Chen Jiayi Zhang Yu Jin Bo Ai School of Electronic and Information Engineering Beijing Jiaotong UniversityBeijing 100044China State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong UniversityBeijing 100044China Henan Joint International Research Laboratory of Intelligent Networking and Data Analysis Zhengzhou UniversityZhengzhou 450001China

A key challenge to the scalable deployment of the energy self-sustainability(ESS)Internet of Everything(IoE)for sixth-generation(6G)networks is juggling massive connectivity and high spectral efficiency(SE).cell-free massive multiple-input multiple-output(CF mmimo)is considered as a promising solution,where many wireless access points perform coherent signal processing to jointly serve the ***,massive connectivity and high SE are difficult to obtain at the same time because of the limited pilot *** solve this problem,we propose a new framework for ESS IoE networks where the user activity detection(UAD)and channel estimation are decoupled.A UAD detector based on deep convolutional neural networks,an initial access scheme,and a scalable power control policy are proposed to enable the practical scalable CF mmimo *** derive novel and exact closed-form expressions of harvested energy and SE with maximum ratio(MR)*** local partial minimum mean-square error and MR combining,simulation results prove that the proposed framework can serve more users,improve the SE performance,and achieve better user fairness for the considered ESS IoE networks.

关键词： 6G network cell-free massive mimo energy self-sustainability Internet of Everything

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基于cell-free massive mimo的非正交多址技术研究

基于Cell-Free Massive MIMO的非正交多址技术研究

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作者：隋秋怡哈尔滨工业大学

学位级别：硕士

由于频率资源的昂贵和稀缺,频谱效率的提升成为了如今无线移动通信的重要研究方向。一方面,cell-free massive mimo（CF-mmimo）作为一种分布式massive mimo技术,相较于集中式massive mimo,它有着更强的抗阴影衰落能力,并能够使小区边... 详细信息

由于频率资源的昂贵和稀缺,频谱效率的提升成为了如今无线移动通信的重要研究方向。一方面,cell-free massive mimo（CF-mmimo）作为一种分布式massive mimo技术,相较于集中式massive mimo,它有着更强的抗阴影衰落能力,并能够使小区边缘用户实现更高的吞吐量,从而大幅度提升频谱效率。另一方面,非正交多址接入技术（Non-orthogonal Multiple Access,NOMA）作为近年来的研究热点之一,能够通过功率复用使多个用户使用相同的时频资源,也被认为是5G时代提升频谱效率的关键技术之一。因此,将NOMA技术应用于CF-mmimo系统可以更进一步地提高频谱效率,满足目前日益增长的通信需求。本文首先介绍了CF-mmimo与NOMA的相关理论。阐述了CF-mmimo的导频发射和信道估计方法,以及下行数据传输阶段的实现方案。介绍了功率域NOMA中使用的叠加码本编码（Superposition Coding,SC）和串行干扰消除（Successive Interference Cancellation,SIC）这两项关键技术,分析了下行链路中NOMA的流程,推导了NOMA的可实现和速率。之后将二者结合,分析了NOMA应用于cell-free massive mimo的实现方案并给出性能分析和仿真验证结果。然后,本文针对莱斯信道下基于CF-mmimo的NOMA技术相关问题进行研究。介绍了所使用的信道模型、莱斯信道下的实现方案,从理论上分析了频谱效率,并针对目前莱斯信道下基于CF-mmimo的NOMA存在的公平性差的问题提出了一种最大化最小频谱效率功率分配算法,从而大幅度提高系统内用户的最小频谱效率。之后,由于目前在CF-mmimo中使用NOMA和OMA分别有各自的优势和劣势,所以本文提出了基于CF-mmimo的OMA与NOMA结合的方案,这种方案更加灵活,而且结合了NOMA与OMA的优势。论文分析了该方案中用户的发射信号、接收信号、信干噪比和频谱效率,并对使用的功率分配算法的原理、推导和算法流程进行研究。最后给出了仿真结果,证明了该方案较单独使用OMA或NOMA在某些场景下更有优势。最后,在结尾总结全文,并指出了目前CF-mmimo与NOMA结合的研究中尚未解决的问题和未来的研究方向。

关键词：大规模天线阵列 cell-free massive mimo 非正交多址

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基于深度强化学习的cell-free massive mimo移动边缘计算卸载算法研究

基于深度强化学习的Cell-Free Massive MIMO移动边缘计算卸载算法...

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作者：章王舜哈尔滨工业大学

学位级别：硕士

移动通信技术追求的一个技术指标是更快的数据传输速率。但目前的蜂窝架构网络却可能对此施加限制。于是一种新的被称为cell-free massive mimo或简称为CF的网络概念被提出。与此同时,随着移动终端设备计算能力的大大增强,一些如VR等的... 详细信息

移动通信技术追求的一个技术指标是更快的数据传输速率。但目前的蜂窝架构网络却可能对此施加限制。于是一种新的被称为cell-free massive mimo或简称为CF的网络概念被提出。与此同时,随着移动终端设备计算能力的大大增强,一些如VR等的计算密集型任务逐渐需要由被移动设备完成。但用户往往希望这些任务能够以低时延被完成,从而为自身带来良好体验。而设备的便携性又会限制其计算能力,使得上述目标很难实现。因此,一种被称为移动边缘计算(Mobile Edge Computation,MEC)的概念被提出。它通过在网络接入侧配备边缘服务器从而代替用户设备执行这些任务来侧面增强用户设备的计算能力。MEC的实现一方面需要较高的信息传输速率来减少传输时延对总时延的影响,另一方面需要用户在任何地点都能获取几乎相同的传输速率。这对传统网络来说是个挑战。本文首先对cell-free massive mimo进行了理论分析,包括不同的信号传输阶段和上行可达频谱效率。通过对得出的上行频谱效率表达式进行数值仿真可以知道,它能够实现较高的频谱效率和较好的用户公平性。这就让CF能够成为MEC基础设施的有力竞争者。而将CF和MEC两者结合就得到了CF-MEC模型。接着,由于CF-MEC网络在接入侧有大量的AP可供服务器的部署,因此决定计算任务去向的计算卸载问题就变得很重要。本文在对现有文献在相关问题的讨论的基础上,分析了现有方法的局限性并据此提出了基于深度强化学习的CFMEC计算卸载算法。本文首先考虑了集中式计算卸载算法。它将计算任务的卸载决策交由网络中心,也就是CPU进行。这一方法通过使用全局信息来优化当前计算任务的卸载对象。在设置了计算任务频繁到达的场景之后,本文对基于深度强化学习的集中式计算卸载方法进行了仿真和比较分析。最后,本文考虑了基于深度强化学习的分布式计算卸载算法。集中式计算卸载引入的额外传输时延在某些情况下会降低用户体验,而分布式计算卸载则能够克服这一缺点。它通过允许用户在合适的时候选择进行本地计算的决策来减少传输时延。通过使用和集中式卸载决策相同的场景,本文仿真分析了分布式计算卸载算法的性能和优缺点。

关键词： cell-free massive mimo MEC 计算卸载深度强化学习

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