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基于Massive MIMO的5G高业务量场景组网方案
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作者 王进 童贞理 郑念 《邮电设计技术》 2024年第1期40-43,共4页
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
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基于位置分配的去蜂窝massive MIMO系统导频分配功率控制算法
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作者 申东 刘家乐 陈丽 《云南大学学报(自然科学版)》 CAS CSCD 北大核心 2024年第3期478-485,共8页
针对去蜂窝(cell free,CF)大规模多输入多输出(multiple-input multiple-output,MIMO)系统中存在严重的导频污染问题,提出了一种基于位置分配的贪婪导频分配功率控制算法(greedy pilot assignment based on location with pilot power c... 针对去蜂窝(cell free,CF)大规模多输入多输出(multiple-input multiple-output,MIMO)系统中存在严重的导频污染问题,提出了一种基于位置分配的贪婪导频分配功率控制算法(greedy pilot assignment based on location with pilot power control,GPABL with PPC).首先,遵循相邻用户不分配相同导频序列的原则进行贪婪导频分配(greedy pilot assignment,GPA);然后,在导频分配的基础上叠加了导频功率控制,选择合理的导频功率控制系数减小信道估计的均方误差.仿真结果表明,将两种方式结合起来进行导频优化,系统的吞吐能力有所提升. 展开更多
关键词 去蜂窝大规模mimo系统 导频污染 导频分配 功率控制
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Deep learning for joint channel estimation and feedback in massive MIMO systems 被引量:1
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作者 Jiajia Guo Tong Chen +3 位作者 Shi Jin Geoffrey Ye Li Xin Wang Xiaolin Hou 《Digital Communications and Networks》 SCIE CSCD 2024年第1期83-93,共11页
The great potentials of massive Multiple-Input Multiple-Output(MIMO)in Frequency Division Duplex(FDD)mode can be fully exploited when the downlink Channel State Information(CSI)is available at base stations.However,th... The great potentials of massive Multiple-Input Multiple-Output(MIMO)in Frequency Division Duplex(FDD)mode can be fully exploited when the downlink Channel State Information(CSI)is available at base stations.However,the accurate CsI is difficult to obtain due to the large amount of feedback overhead caused by massive antennas.In this paper,we propose a deep learning based joint channel estimation and feedback framework,which comprehensively realizes the estimation,compression,and reconstruction of downlink channels in FDD massive MIMO systems.Two networks are constructed to perform estimation and feedback explicitly and implicitly.The explicit network adopts a multi-Signal-to-Noise-Ratios(SNRs)technique to obtain a single trained channel estimation subnet that works well with different SNRs and employs a deep residual network to reconstruct the channels,while the implicit network directly compresses pilots and sends them back to reduce network parameters.Quantization module is also designed to generate data-bearing bitstreams.Simulation results show that the two proposed networks exhibit excellent performance of reconstruction and are robust to different environments and quantization errors. 展开更多
关键词 Channel estimation CSI feedback Deep learning massive mimo FDD
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Performance Analysis of ZF and RZF in Low-Resolution ADC/DAC Massive MIMO Systems
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作者 Talha Younas Shen Jin +4 位作者 Muluneh Mekonnen Gao Mingliang Saqib Saleem Sohaib Tahir Mahrukh Liaqat 《China Communications》 SCIE CSCD 2024年第8期115-126,共12页
Large number of antennas and higher bandwidth usage in massive multiple-input-multipleoutput(MIMO)systems create immense burden on receiver in terms of higher power consumption.The power consumption at the receiver ra... Large number of antennas and higher bandwidth usage in massive multiple-input-multipleoutput(MIMO)systems create immense burden on receiver in terms of higher power consumption.The power consumption at the receiver radio frequency(RF)circuits can be significantly reduced by the application of analog-to-digital converter(ADC)of low resolution.In this paper we investigate bandwidth efficiency(BE)of massive MIMO with perfect channel state information(CSI)by applying low resolution ADCs with Rician fadings.We start our analysis by deriving the additive quantization noise model,which helps to understand the effects of ADC resolution on BE by keeping the power constraint at the receiver in radar.We also investigate deeply the effects of using higher bit rates and the number of BS antennas on bandwidth efficiency(BE)of the system.We emphasize that good bandwidth efficiency can be achieved by even using low resolution ADC by using regularized zero-forcing(RZF)combining algorithm.We also provide a generic analysis of energy efficiency(EE)with different options of bits by calculating the energy efficiencies(EE)using the achievable rates.We emphasize that satisfactory BE can be achieved by even using low-resolution ADC/DAC in massive MIMO. 展开更多
关键词 low-bit analog-digital converter massive(multiple-input-multiple-output)mimo minimum mean square error(MMSE) regularized zero forcing zero forcing
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Optimization of resource allocation in FDD massive MIMO systems
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作者 Jun Cai Chuan Yin Youwei Ding 《Digital Communications and Networks》 SCIE CSCD 2024年第1期117-125,共9页
The performance of massive MIMO systems relies heavily on the availability of Channel State Information at the Transmitter(CSIT).A large amount of work has been devoted to reducing the CSIT acquisition overhead at the... The performance of massive MIMO systems relies heavily on the availability of Channel State Information at the Transmitter(CSIT).A large amount of work has been devoted to reducing the CSIT acquisition overhead at the pilot training and/or CsI feedback stage.In fact,the downlink communication generally includes three stages,i.e.,pilot training,CsI feedback,and data transmission.These three stages are mutually related and jointly determine the overall system performance.Unfortunately,there exist few studies on the reduction of csIT acquisition overhead from the global point of view.In this paper,we integrate the Minimum Mean Square Error(MMSE)channel estimation,Random Vector Quantization(RVQ)based limited feedback and Maximal Ratio Combining(MRC)precoding into a unified framework for investigating the resource allocation problem.In particular,we first approximate the covariance matrix of the quantization error with a simple expression and derive an analytical expression of the received Signal-to-Noise Ratio(SNR)based on the deterministic equivalence theory.Then the three performance metrics(the spectral efficiency,energy efficiency,and total energy consumption)oriented problems are formulated analytically.With practical system requirements,these three metrics can be collaboratively optimized.Finally,we propose an optimization solver to derive the optimal partition of channel coherence time.Experiment results verify the benefits of the proposed resource allocation schemes under three different scenarios and illustrate the tradeoff of resource allocation between three stages. 展开更多
关键词 massive mimo FDD CSIT Resource allocation
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A Correlation-Based Stochastic Model for Massive MIMO Channel
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作者 Yang Liu Gang Li Chengxiang Wang 《China Communications》 SCIE CSCD 2024年第1期175-187,共13页
In this paper,the channel impulse response matrix(CIRM)can be expressed as a sum of couplings between the steering vectors at the base station(BS)and the eigenbases at the mobile station(MS).Nakagami distribution was ... In this paper,the channel impulse response matrix(CIRM)can be expressed as a sum of couplings between the steering vectors at the base station(BS)and the eigenbases at the mobile station(MS).Nakagami distribution was used to describe the fading of the coupling between the steering vectors and the eigenbases.Extensive measurements were carried out to evaluate the performance of this proposed model.Furthermore,the physical implications of this model were illustrated and the capacities are analyzed.In addition,the azimuthal power spectrum(APS)of several models was analyzed.Finally,the channel hardening effect was simulated and discussed.Results showed that the proposed model provides a better fit to the measured results than the other CBSM,i.e.,Weichselberger model.Moreover,the proposed model can provide better tradeoff between accuracy and complexity in channel synthesis.This CIRM model can be used for massive MIMO design in the future communication system design. 展开更多
关键词 CBSM channel capacity channel hardening channel modeling massive mimo
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Network-Assisted Full-Duplex Cell-Free mmWave Massive MIMO Systems with DAC Quantization and Fronthaul Compression
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作者 Li Jiamin Fan Qingrui +4 位作者 Zhang Yu Zhu Pengcheng Wang Dongming Wu Hao You Xiaohu 《China Communications》 SCIE CSCD 2024年第11期75-87,共13页
In this paper,we investigate networkassisted full-duplex(NAFD)cell-free millimeter-wave(mmWave)massive multiple-input multiple-output(MIMO)systems with digital-to-analog converter(DAC)quantization and fronthaul compre... In this paper,we investigate networkassisted full-duplex(NAFD)cell-free millimeter-wave(mmWave)massive multiple-input multiple-output(MIMO)systems with digital-to-analog converter(DAC)quantization and fronthaul compression.We propose to maximize the weighted uplink and downlink sum rate by jointly optimizing the power allocation of both the transmitting remote antenna units(T-RAUs)and uplink users and the variances of the downlink and uplink fronthaul compression noises.To deal with this challenging problem,we further apply a successive convex approximation(SCA)method to handle the non-convex bidirectional limited-capacity fronthaul constraints.The simulation results verify the convergence of the proposed SCA-based algorithm and analyze the impact of fronthaul capacity and DAC quantization on the spectral efficiency of the NAFD cell-free mmWave massive MIMO systems.Moreover,some insightful conclusions are obtained through the comparisons of spectral efficiency,which shows that NAFD achieves better performance gains than cotime co-frequency full-duplex cloud radio access network(CCFD C-RAN)in the cases of practical limited-resolution DACs.Specifically,their performance gaps with 8-bit DAC quantization are larger than that with1-bit DAC quantization,which attains a 5.5-fold improvement. 展开更多
关键词 cell-free massive mimo DAC quantization millimeter-wave network-assisted full-duplex
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Power Allocation for SE Maximization in Uplink Massive MIMO System Under Minimum Rate Constraint
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作者 Wang Hui Yu Xiangbin +1 位作者 Liu Fuyuan Bai Jiawei 《China Communications》 SCIE CSCD 2024年第3期104-117,共14页
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 channel.The SE optimization problem i... 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 channel.The SE optimization problem is formulated under the constraints of maximum power and minimum rate of each user.Then,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 complexity.Since 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 constraints.This suboptimal scheme only needs single-layer iteration,thus has lower complexity than the near-optimal scheme.Finally,we joint design the pilot power and data power to further improve the performance,and propose an two-stage algorithm to obtain joint PA.Simulation results verify the effectiveness of the proposed schemes,and superior SE performance is achieved. 展开更多
关键词 imperfect CSI massive mimo minimum rate constraint power allocation spectral efficiency
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Deep Reinforcement Learning Based Joint Cooperation Clustering and Downlink Power Control for Cell-Free Massive MIMO
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作者 Du Mingjun Sun Xinghua +2 位作者 Zhang Yue Wang Junyuan Liu Pei 《China Communications》 SCIE CSCD 2024年第11期1-14,共14页
In recent times,various power control and clustering approaches have been proposed to enhance overall performance for cell-free massive multipleinput multiple-output(CF-mMIMO)networks.With the emergence of deep reinfo... In recent times,various power control and clustering approaches have been proposed to enhance overall performance for cell-free massive multipleinput multiple-output(CF-mMIMO)networks.With the emergence of deep reinforcement learning(DRL),significant progress has been made in the field of network optimization as DRL holds great promise for improving network performance and efficiency.In this work,our focus delves into the intricate challenge of joint cooperation clustering and downlink power control within CF-mMIMO networks.Leveraging the potent deep deterministic policy gradient(DDPG)algorithm,our objective is to maximize the proportional fairness(PF)for user rates,thereby aiming to achieve optimal network performance and resource utilization.Moreover,we harness the concept of“divide and conquer”strategy,introducing two innovative methods termed alternating DDPG(A-DDPG)and hierarchical DDPG(H-DDPG).These approaches aim to decompose the intricate joint optimization problem into more manageable sub-problems,thereby facilitating a more efficient resolution process.Our findings unequivo-cally showcase the superior efficacy of our proposed DDPG approach over the baseline schemes in both clustering and downlink power control.Furthermore,the A-DDPG and H-DDPG obtain higher performance gain than DDPG with lower computational complexity. 展开更多
关键词 cell-free massive mimo CLUSTERING deep reinforcement learning power control
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Off-Grid Compressed Channel Estimation with Parallel Interference Cancellation for Millimeter Wave Massive MIMO
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作者 Liu Jinru Tian Yongqing +1 位作者 Liu Danpu Zhang Zhilong 《China Communications》 SCIE CSCD 2024年第3期51-65,共15页
Millimeter wave(mmWave)massive multiple-input multiple-output(MIMO)plays an important role in the fifth-generation(5G)mobile communications and beyond wireless communication systems owing to its potential of high capa... Millimeter wave(mmWave)massive multiple-input multiple-output(MIMO)plays an important role in the fifth-generation(5G)mobile communications and beyond wireless communication systems owing to its potential of high capacity.However,channel estimation has become very challenging due to the use of massive MIMO antenna array.Fortunately,the mmWave channel has strong sparsity in the spatial angle domain,and the compressed sensing technology can be used to convert the original channel matrix into the sparse matrix of discrete angle grid.Thus the high-dimensional channel matrix estimation is transformed into a sparse recovery problem with greatly reduced computational complexity.However,the path angle in the actual scene appears randomly and is unlikely to be completely located on the quantization angle grid,thus leading to the problem of power leakage.Moreover,multiple paths with the random distribution of angles will bring about serious interpath interference and further deteriorate the performance of channel estimation.To address these off-grid issues,we propose a parallel interference cancellation assisted multi-grid matching pursuit(PIC-MGMP)algorithm in this paper.The proposed algorithm consists of three stages,including coarse estimation,refined estimation,and inter-path cyclic iterative inter-ference cancellation.More specifically,the angular resolution can be improved by locally refining the grid to reduce power leakage,while the inter-path interference is eliminated by parallel interference cancellation(PIC),and the two together improve the estimation accuracy.Simulation results show that compared with the traditional orthogonal matching pursuit(OMP)algorithm,the normalized mean square error(NMSE)of the proposed algorithm decreases by over 14dB in the case of 2 paths. 展开更多
关键词 channel estimation compressed sensing inter-path interference millimeter wave massive mimo OFF-GRID parallel interference cancellation
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Optimal AP Deployment in Cell-Free Massive MIMO Systems with LoS/NLoS Transmissions:A Stochastic Geometry Approach
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作者 Jiang Ling Zhang Qi Zhu Hongbo 《China Communications》 SCIE CSCD 2024年第9期146-158,共13页
Cell-free massive multiple-input multipleoutput(MIMO)is a promising technology for future wireless communications,where a large number of distributed access points(APs)simultaneously serve all users over the same time... Cell-free massive multiple-input multipleoutput(MIMO)is a promising technology for future wireless communications,where a large number of distributed access points(APs)simultaneously serve all users over the same time-frequency resources.Since users and APs may locate close to each other,the line-of-sight(Lo S)transmission occurs more frequently in cell-free massive MIMO systems.Hence,in this paper,we investigate the cell-free massive MIMO system with Lo S and non-line-of-sight(NLo S)transmissions,where APs and users are both distributed according to Poisson point process.Using tools from stochastic geometry,we derive a tight lower bound for the user downlink achievable rate and we further obtain the energy efficiency(EE)by considering the power consumption on downlink payload transmissions and circuitry dissipation.Based on the analysis,the optimal AP density and AP antenna number that maximize the EE are obtained.It is found that compared with the previous work that only considers NLo S transmissions,the actual optimal AP density should be much smaller,and the maximized EE is actually much higher. 展开更多
关键词 cell-free massive mimo energy efficiency LoS/NLoS transmissions stochastic geometry
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Turbo Message Passing Based Burst Interference Cancellation for Data Detection in Massive MIMO-OFDM Systems
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作者 Wenjun Jiang Zhihao Ou +1 位作者 Xiaojun Yuan Li Wang 《China Communications》 SCIE CSCD 2024年第2期143-154,共12页
This paper investigates the fundamental data detection problem with burst interference in massive multiple-input multiple-output orthogonal frequency division multiplexing(MIMO-OFDM) systems. In particular, burst inte... This paper investigates the fundamental data detection problem with burst interference in massive multiple-input multiple-output orthogonal frequency division multiplexing(MIMO-OFDM) systems. In particular, burst interference may occur only on data symbols but not on pilot symbols, which means that interference information cannot be premeasured. To cancel the burst interference, we first revisit the uplink multi-user system and develop a matrixform system model, where the covariance pattern and the low-rank property of the interference matrix is discussed. Then, we propose a turbo message passing based burst interference cancellation(TMP-BIC) algorithm to solve the data detection problem, where the constellation information of target data is fully exploited to refine its estimate. Furthermore, in the TMP-BIC algorithm, we design one module to cope with the interference matrix by exploiting its lowrank property. Numerical results demonstrate that the proposed algorithm can effectively mitigate the adverse effects of burst interference and approach the interference-free bound. 展开更多
关键词 burst interference cancellation data detection massive multiple-input multiple-output(mimo) message passing orthogonal frequency division multiplexing(OFDM)
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Low-complexity signal detection for massive MIMO systems via trace iterative method
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作者 IMRAN A.Khoso ZHANG Xiaofei +2 位作者 ABDUL Hayee Shaikh IHSAN A.Khoso ZAHEER Ahmed Dayo 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2024年第3期549-557,共9页
Linear minimum mean square error(MMSE)detection has been shown to achieve near-optimal performance for massive multiple-input multiple-output(MIMO)systems but inevitably involves complicated matrix inversion,which ent... Linear minimum mean square error(MMSE)detection has been shown to achieve near-optimal performance for massive multiple-input multiple-output(MIMO)systems but inevitably involves complicated matrix inversion,which entails high complexity.To avoid the exact matrix inversion,a considerable number of implicit and explicit approximate matrix inversion based detection methods is proposed.By combining the advantages of both the explicit and the implicit matrix inversion,this paper introduces a new low-complexity signal detection algorithm.Firstly,the relationship between implicit and explicit techniques is analyzed.Then,an enhanced Newton iteration method is introduced to realize an approximate MMSE detection for massive MIMO uplink systems.The proposed improved Newton iteration significantly reduces the complexity of conventional Newton iteration.However,its complexity is still high for higher iterations.Thus,it is applied only for first two iterations.For subsequent iterations,we propose a novel trace iterative method(TIM)based low-complexity algorithm,which has significantly lower complexity than higher Newton iterations.Convergence guarantees of the proposed detector are also provided.Numerical simulations verify that the proposed detector exhibits significant performance enhancement over recently reported iterative detectors and achieves close-to-MMSE performance while retaining the low-complexity advantage for systems with hundreds of antennas. 展开更多
关键词 signal detection LOW-COMPLEXITY linear minimum mean square error(MMSE) massive multiple-input multiple-output(mimo) trace iterative method(TIM)
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基于Massive MIMO的5G基站能效优化研究
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作者 吴远 郝佳佳 +2 位作者 朱文涛 王西点 张晨曦 《邮电设计技术》 2024年第7期56-59,共4页
5G网络已成熟商用,但是其能效问题一直影响着5G发展,MassiveMIMO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。... 5G网络已成熟商用,但是其能效问题一直影响着5G发展,MassiveMIMO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。 展开更多
关键词 能效优化 数字孪生 massive mimo 蚁群算法
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地铁隧道有限空间Massive MIMO性能研究 被引量:1
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作者 王树奇 吕方 《通信技术》 2023年第3期263-268,共6页
基于实际场景测量,对地铁隧道有限空间Massive MIMO性能进行了研究。采用复用天线阵列法实现收发同步切换分时虚拟MIMO测量。基于测量数据,主要分析了3.5 GHz和5.6 GHz频段Massive MIMO信道在隧道场景的性能,研究了信道矩阵的特征值分... 基于实际场景测量,对地铁隧道有限空间Massive MIMO性能进行了研究。采用复用天线阵列法实现收发同步切换分时虚拟MIMO测量。基于测量数据,主要分析了3.5 GHz和5.6 GHz频段Massive MIMO信道在隧道场景的性能,研究了信道矩阵的特征值分布和条件数,着重分析了不同收发天线距离对Massive MIMO信道容量的影响,考虑了基于信噪比的有效秩选择方法。研究结果表明,在3.5 GHz及5.6 GHz频段上,Massive MIMO信道矩阵条件数的范围处在30 dB至55 dB之间,信道容量有较大的提升,且信道矩阵的有效秩随收发机距离增大的衰减趋势明显。以上结果对隧道场景下一代无线通信系统的设计与部署提供了依据。 展开更多
关键词 massive mimo 信道测量 特征值 信道容量
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Joint Flexible Duplexing and Power Allocation with Deep Reinforcement Learning in Cell-Free Massive MIMO System 被引量:5
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作者 Danhao Deng Chaowei Wang +2 位作者 Zhi Zhang Lihua Li Weidong Wang 《China Communications》 SCIE CSCD 2023年第4期73-85,共13页
Network-assisted full duplex(NAFD)cellfree(CF)massive MIMO has drawn increasing attention in 6G evolvement.In this paper,we build an NAFD CF system in which the users and access points(APs)can flexibly select their du... Network-assisted full duplex(NAFD)cellfree(CF)massive MIMO has drawn increasing attention in 6G evolvement.In 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 efficiency.Then we formulate a joint flexible duplexing and power allocation problem to balance the user fairness and system spectral efficiency.We further transform the problem into a probability optimization to accommodate the shortterm communications.In 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 policy.Simulation results demonstrate that the A3C-based scheme is superior to the baseline schemes in term of the complexity,accumulated log spectral efficiency,and stability. 展开更多
关键词 cell-free massive mimo flexible duplexing sum fair spectral efficiency deep reinforcement learning asynchronous advantage actor-critic
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DQL-Based Intelligent Scheduling Algorithm for Automatic Driving in Massive MIMO V2I Scenarios 被引量:2
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作者 Yong Liao Zisong Yin +1 位作者 Zhijing Yang Xuanfan Shen 《China Communications》 SCIE CSCD 2023年第3期18-26,共9页
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 ever... 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 transmission.In 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 scenario.The 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. 展开更多
关键词 NR autonomous driving V2I link adap-tation massive mimo deep Q-learning
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Grant-Free Random Access in Pilot-Reused Multicell Massive MIMO Systems with Backoff Mechanisms 被引量:1
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作者 Qi Zhang Jun Zhang Shi Jin 《China Communications》 SCIE CSCD 2023年第9期185-195,共11页
Grant-free random access(RA)is attractive for future network due to the minimized access delay.In this paper,we investigate the grantfree RA in multicell massive multiple-input multipleoutput(MIMO)systems with pilot r... Grant-free random access(RA)is attractive for future network due to the minimized access delay.In this paper,we investigate the grantfree RA in multicell massive multiple-input multipleoutput(MIMO)systems with pilot reuse.With backoff mechanism,user equipments(UEs)in each cell are randomly activated,and active UEs randomly select orthogonal pilots from a predefined pilot pool,which results in a random pilot contamination among cells.With the help of indicators that capture the uncertainties of UE activation and pilot selection,we derive a closed-form approximation of the spectral efficiency per cell after averaging over the channel fading as well as UEs’random behaviors.Based on the analysis,the optimal backoff parameter and pilot length that maximize the spectral efficiency can be obtained.We find that the backoff mechanism is necessary for the system with large number of UEs,as it can bring significant gains on the spectral efficiency.Moreover,as UE number grows,more backoff time is needed. 展开更多
关键词 backoff mechanism grant-free RA multicell massive mimo
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On Dynamic Channel Emulation in Sector MPAC for Over-the-Air Testing of Beamformed Massive MIMO Devices 被引量:1
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作者 Xiaochen Chen Heng Wang +2 位作者 Weimin Wang Zheng Liu Yuanan Liu 《China Communications》 SCIE CSCD 2023年第4期41-56,共16页
In this article,novel emulation strategies for the sectored multiple probe anechoic chamber(SMPAC)are proposed to enable the reliable evaluation of the massive multiple-input multiple-output(MIMO)device operating at b... In this article,novel emulation strategies for the sectored multiple probe anechoic chamber(SMPAC)are proposed to enable the reliable evaluation of the massive multiple-input multiple-output(MIMO)device operating at beamforming mode,which requires a realistic non-stationary channel environment.For the dynamic propagation emulation,an efficient closed-form probe weighting strategy minimizing the power angular spectrum(PAS)emulation errors is derived,substantially reducing the associated computational complexity.On the other hand,a novel probe selection algorithm is proposed to reproduce a more accurate fading environment.Various standard channel models and setup configurations are comprehensively simulated to validate the capacity of the proposed methods.The simulation results show that more competent active probes are selected with the proposed method compared to the conventional algorithms.Furthermore,the derived closedform probe weighting strategy offers identical accuracy to that obtained with complicated numerical optimization.Moreover,a realistic dynamic channel measured in an indoor environment is reconstructed with the developed methodologies,and 95.6%PAS similarity can be achieved with 6 active probes.The satisfactory results demonstrate that the proposed algorithms are suitable for arbitrary channel emulation. 展开更多
关键词 BEAMFORMING channel emulation massive mimo device multiple probe anechoic chamber(MPAC) over-the-air testing
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Multi-Panel Extra-Large Scale MIMO Based Joint Activity Detection and Channel Estimation for Near-Field Massive IoT Access 被引量:1
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作者 Zhen Gao Hanlin Xiu +4 位作者 Yikun Mei Anwen Liao Malong Ke Chun Hu Mohamed-Slim Alouini 《China Communications》 SCIE CSCD 2023年第5期232-243,共12页
The extra-large scale multiple-input multiple-output(XL-MIMO)for the beyond fifth/sixth generation mobile communications is a promising technology to provide Tbps data transmission and stable access service.However,th... The extra-large scale multiple-input multiple-output(XL-MIMO)for the beyond fifth/sixth generation mobile communications is a promising technology to provide Tbps data transmission and stable access service.However,the extremely large antenna array aperture arouses the channel near-field effect,resulting in the deteriorated data rate and other challenges in the practice communication systems.Meanwhile,multi-panel MIMO technology has attracted extensive attention due to its flexible configuration,low hardware cost,and wider coverage.By combining the XL-MIMO and multi-panel array structure,we construct multi-panel XL-MIMO and apply it to massive Internet of Things(IoT)access.First,we model the multi-panel XL-MIMO-based near-field channels for massive IoT access scenarios,where the electromagnetic waves corresponding to different panels have different angles of arrival/departure(AoAs/AoDs).Then,by exploiting the sparsity of the near-field massive IoT access channels,we formulate a compressed sensing based joint active user detection(AUD)and channel estimation(CE)problem which is solved by AMP-EM-MMV algorithm.The simulation results exhibit the superiority of the AMP-EM-MMV based joint AUD and CE scheme over the baseline algorithms. 展开更多
关键词 extra-large scale mimo massive IoT access active user detection channel estimation multipanel approximate message passing
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