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Power Allocation for SE Maximization in Uplink massive mimo System Under Minimum Rate Constraint

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China Communications 2024年第3期21卷 104-117页

作者： Wang Hui Yu Xiangbin Liu Fuyuan Bai Jiawei College of Electronic and Information Engineering Nanjing University of Aeronautics and AstronauticsNanjing 211106China Key Laboratory of Wireless Sensor Network and Communication Shanghai Institute of Microsystem and Information TechnologyChinese Academy of SciencesShanghai 200050China

In this paper,we optimize the spectrum efficiency(SE)of uplink massive multiple-input multiple-output(mimo)system with imperfect channel state information(CSI)over Rayleigh fading *** SE optimization problem is formulated under the constraints of maximum power and minimum rate of each ***,we develop a near-optimal power allocation(PA)scheme by using the successive convex approximation(SCA)method,Lagrange multiplier method,and block coordinate descent(BCD)method,and it can obtain almost the same SE as the benchmark scheme with lower *** this scheme needs three-layer iteration,a suboptimal PA scheme is developed to further reduce the complexity,where the characteristic of massive mimo(i.e.,numerous receive antennas)is utilized for convex reformulation,and the rate constraint is converted to linear *** suboptimal scheme only needs single-layer iteration,thus has lower complexity than the near-optimal ***,we joint design the pilot power and data power to further improve the performance,and propose an two-stage algorithm to obtain joint *** results verify the effectiveness of the proposed schemes,and superior SE performance is achieved.

关键词： imperfect CSI massive mimo minimum rate constraint power allocation spectral efficiency

基于massive mimo的5G基站能效优化研究

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邮电设计技术 2024年第7期 56-59页

作者：吴远郝佳佳朱文涛王西点张晨曦中国移动通信集团设计院有限公司浙江分公司中国移动通信集团设计院有限公司

5G网络已成熟商用，但是其能效问题一直影响着5G发展，massive mimo技术是提升网络覆盖、用户体验和系统容量的核心技术，可作为提升5G网络能效的一种手段。开展了基于蚁群算法的迭代寻优算法的研究，解决海量mimo参数组合最优解迭代问... 详细信息

5G网络已成熟商用，但是其能效问题一直影响着5G发展，massive mimo技术是提升网络覆盖、用户体验和系统容量的核心技术，可作为提升5G网络能效的一种手段。开展了基于蚁群算法的迭代寻优算法的研究，解决海量mimo参数组合最优解迭代问题。同时构建了基于数字孪生技术的功率优化模型，实现5G网络能效的优化。模型实验和现网验证结果显示：该算法能够达到预期效果，为后续基站的能效优化和mimo智慧优化演进提供参考。

关键词：能效优化数字孪生 massive mimo 蚁群算法

基于massive mimo的5G高业务量场景组网方案

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邮电设计技术 2024年第1期 40-43页

作者：王进童贞理郑念中国联通重庆分公司重庆401121

针对5G用户量大、流量密度大等高密重载特殊场景,引入分布式massive mimo技术,给出典型场景的速率和容量提升方案,并对方案进行了验证。最后总结了典型场景的组网应用建议,对提升5G用户感知,促进5G市场发展具有重要意义。

关键词： massive mimo 5G 高业务量场景

Robust online energy efficiency optimization for distributed multi-cell massive mimo networks

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Science China(Information Sciences) 2023年第3期66卷 239-252页

作者： Li YOU Yufei HUANG Wen ZHONG Wenjin WANG Xiqi GAO National Mobile Communications Research Laboratory Southeast University Purple Mountain Laboratories

This paper studies the energy efficiency(EE) oriented precoding design in multi-cell massive multiple-input multiple-output(mimo) systems, with only statistical channel state information(CSI) at the transmitter. During the transmission, as the channel varies dynamically with time and the previously obtained CSI becomes outdated, the base stations must adjust their transmit policies accordingly. To tackle this issue, we propose an online EE maximization algorithm that can achieve a no-regret transmission; i.e.,the performance of this online method gradually approaches that of the fixed offline method which has full knowledge of the future CSI. Specifically, we first construct the online EE optimization problem in a distributed way to reduce the information required to be exchanged between cells. Then, we apply the largedimensional random matrix theory to lower the calculation complexity, and the Charnes-Cooper transform to address the nonconvexity of the problem, respectively. The online gradient ascent method is utilized to perform this no-regret power allocation strategy based on all past CSI. We also assess the robustness of the algorithm to estimation error of statistical CSI under some mild conditions which can usually be satisfied in practice. Numerical results demonstrate the no-regret property and the robustness of the proposed online algorithm for energy efficient multi-cell massive mimo transmission.

关键词： energy efficiency statistical CSI multi-cell mimo massive mimo online gradient ascent distributed processing robust transmission

Low Complexity Detection Algorithms Based on ADMIN for massive mimo

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China Communications 2023年第11期20卷 67-77页

作者： Shuchao Mi Jianyong Zhang Fengju Fan Baorui Yan Muguang Wang Institute of Lightwave Technology Beijing Jiaotong UniversityBeijing 100044China Key Lab of All Optical Network and Advanced Telecommunication of EMC Beijing Jiaotong UniversityBeijing 100044China

This paper proposes the alternating direction method of multipliers-based infinity-norm(ADMIN) with threshold(ADMIN-T) and with percentage(ADMIN-P) detection algorithms,which make full use of the distribution of the signal to interference plus noise ratio(SINR) for an uplink massive mimo *** ADMIN-T and ADMIN-P detection algorithms are improved visions of the ADMIN detection algorithm,in which an appropriate SINR threshold in the ADMIN-T detection algorithm and a certain percentage in the ADMIN-P detection algorithm are designed to reduce the overall computational *** detected symbols are divided into two parts by the SINR threshold which is based on the cumulative probability density function(CDF) of SINR and a percentage,*** symbols in higher SINR part are detected by *** interference of these symbols is then cancelled by successive interference cancellation(SIC).Afterwards the remaining symbols with low SINR are iteratively detected by *** simulation results show that the ADMIIN-T and the ADMIN-P detection algorithms provide a significant performance gain compared with some recently proposed detection *** addition,the computational complexity of ADMIN-T and ADMIN-P are significantly ***,in the case of same number of transceiver antennas,the proposed algorithms have a higher performance compared with the case of asymmetric transceiver antennas.

关键词： ADMIN low complexity detection algo-rithm massive mimo MMSE SINR

DQL-Based Intelligent Scheduling Algorithm for Automatic Driving in massive mimo V2I Scenarios

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China Communications 2023年第3期20卷 18-26页

作者： Yong Liao Zisong Yin Zhijing Yang Xuanfan Shen School of Microelectronics and Communication Engineering Chongqing UniversityChongqing 400044China

Connected and autonomous vehicle(CAV)vehicle to infrastructure(V2I)scenarios have more stringent requirements on the communication rate,delay,and reliability of the Internet of vehicles(Io V).New radio vehicle to everything(NR-V2X)adopts link adaptation(LA)to improve the efficiency and reliability of road safety information *** order to solve the problem that the existing LA scheduling algorithms cannot adapt to the Doppler shift and complex fast time-varying channel in V2I scenario,resulting in low reliability of information transmission,this paper proposes a deep Q-learning(DQL)-based massive multiple-input multiple-output(mimo)LA scheduling algorithm for autonomous driving V2I *** algorithm combines deep neural network(DNN)with Q-learning(QL)algorithm,which is used for joint scheduling of modulation and coding scheme(MCS)and space division multiplexing(SDM).The system simulation results show that the algorithm proposed in this paper can fully adapt to the different channel environment in the V2I scenario,and select the optimal MCS and SDM for the transmission of road safety information,thereby the accuracy of road safety information transmission is improved,collision accidents can be avoided,and bring a good autonomous driving experience.

关键词： NR autonomous driving V2I link adap-tation massive mimo deep Q-learning

A Universal Hybrid Precoding Scheme for massive mimo Communications

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China Communications 2022年第11期19卷 160-178页

作者： Yimeng Feng Yi Jiang Mahesh K.Varanasi Key Laboratory for Information Science of Electromagnetic Waves(MoE) School of Information Science and TechnologyFudan UniversityShanghai 200433China the Department of Electrical Computer and Energy EngineeringUniversity of ColoradoBoulderColorado 80309-0425

Based on an analog radio frequency(RF)network,hybrid precoding(HPC)for massive mimo can achieve very high spectral efficiencies with moderate hardware cost and power *** the extensive research efforts in recent years,the practioners are still looking for HPCs that are efficient and *** this paper,we present a new method termed as the universal hybrid precoding(UHP),which is nearly optimal,computationally efficient,and applicable to various types of RF network(thus,the name universal):the components of the network can be phase shifters(with finite or infinite resolutions),switches,or their combinations;the topology of the network can be fully-connected or *** the standard UHP,we also propose a simplified version termed as sUHP to trade a negligible performance loss for much reduced computational *** analysis shows that the computational complexity of the proposed UHP/sUHP is one to two orders of magnitude lower than the state-of-theart *** results verify the(near-)optimality of the proposed UHP scheme for various forms of the analog networks.

关键词： hybrid beamforming massive mimo phase-shifter network switch network

Optimal Hybrid Precoding Based QoE for Partially Structured massive mimo System

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Computers, Materials & Continua 2022年第4期71卷 1887-1902页

作者： Farung Samklang Peerapong Uthansakul Monthippa Uthansakul Patikorn Anchuen School of Telecommunication Engineering Suranaree University of TechnologyNakhon Ratchasima30000Thailand

Precoding is a beamforming technique that supports multi-streamtransmission in which the RF chain plays a significant role as a digital precoding at the receiver for wireless communication. The traditional precodingcontains only digital signal processing and each antenna connects to each RFchain, which provides high transmission efficiency but high cost and hardwarecomplexity. Hybrid precoding is one of the most popular massive multipleinput multiple output (mimo) techniques that can save costs and avoid usingcomplex hardware. At present, network services are currently in focus with awide range of traffic volumes. In terms of the Quality of Service (QoS), it iscritical that service providers pay a lot of attention to this parameter and itsrelationship to Quality of Experience (QoE) which is the measurement of theoverall level of user satisfaction. Therefore, this paper proposes hybrid precoding of a partially structured system to improve transmission efficiency andallocate resources to provide network services to users for increasing the usersatisfaction under power constraints that optimize the quality of basebandprecoding and radio frequency (RF) precoding by minimizing alternatingalgorithms. We focus on the web browsing, video, and Voice over IP (VOIP)services. Also, a Mean Opinion Score (MOS) is employed to measure thelevel of user satisfaction. The results show that the partially structured systemprovides a good user satisfaction with the network’s services. The partiallystructured system provides high energy efficiency up to 85%. Considering webservice, the partially structured system for 10 users provides MOS at 3.21 whichis higher than 1.75 of fully structured system.

关键词： massive mimo quality of experience(QoE) mean opinion score(MOS) quality of service(QoS) hybrid precoding partially structured system

An energy-efficient resource allocation strategy in massive mimo-enabled vehicular edge computing networks

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高置信计算(英文) 2023年第3期3卷 40-49页

作者： Yibin Xie Lei Shi Zhenchun Wei Juan Xu Yang Zhang School of Computer Science and Information Engineering Hefei University of TechnologyHefei 230009China Engineering Research Center of Safety Critical Industrial Measurement and Control Technology Ministry of EducationHefei 230009China Hefei Origin IoT Technology Co. LtdHefei 230088China

The vehicular edge computing(VEC)is a new paradigm that allows vehicles to offload computational tasks to base stations(BSs)with edge servers for *** general,the VEC paradigm uses the 5G for wireless communications,where the massive multi-input multi-output(mimo)technique will be ***,considering in the VEC environment with many vehicles,the energy consumption of BS may be very *** this paper,we study the energy optimization problem for the massive mimo-based VEC *** at reducing the relevant BS energy consumption,we first propose a joint optimization problem of computation resource allocation,beam allocation and vehicle grouping *** the original problem is hard to be solved directly,we try to split the original problem into two subproblems and then design a heuristic algorithm to solve *** results show that our proposed algorithm efficiently reduces the BS energy consumption compared to other schemes.

关键词： Vehicular edge computing massive mimo Resource allocation Energy-efficient