大规模MIMO加权正交匹配追踪信道估计算法  

Weighted Orthogonal Matching Pursuit Channel Estimation Algorithm for Massive MIMO Systems

作　　者：孙泽宇[1,2] 吕治国 SUN Zeyu;LV Zhiguo(School of Computer and Information Engineering,Luoyang Institute of Science and Technology,Luoyang,Henan 471023,China;Luoyang Key Laboratory of Intelligent Agriculture Husbandry Sensor Networks,Luoyang,Henan 471023,China;State Key Laboratory of Integrated Service Networks,Xidian University,Xi’an 710071,China)

机构地区：[1]洛阳理工学院计算机与信息工程学院,河南洛阳471023 [2]洛阳智能农牧业传感网重点实验室,河南洛阳471023 [3]西安电子科技大学综合业务网理论及关键技术国家重点实验室,西安710071

出　　处：《计算机工程与应用》2020年第5期118-124,共7页Computer Engineering and Applications

基　　金：国家自然科学基金河南省联合基金（No.U1604149）;河南省教育厅自然科学重点基金（No.19A520006）;河南省教育厅青年骨干教师资助项目（No.2016GGJS-158）;洛阳理工学院高层次人才资助计划（No.2017BZ07）

摘　　要：针对大规模多输入多输出系统基站天线数目众多,移动用户很难实时精确完成信道估计等问题。提出了一种加权的正交匹配追踪算法。该算法在每次迭代过程中,计算得到的估计信号值由当前残差信号估计值和迭代之前估计值两部分组合而成;分别对当前残差信号估计值和迭代之前估计值设置不同的权值,以提高信号在低信噪比情况下的估值精度;通过调整不同迭代次数权值大小,可以提升信号在不同信噪比情况下的计算精度。仿真结果表明,在不同的信噪比情况下,该算法都可以获得比标准正交匹配追踪算法更高的估计精度。Massive Multiple Input Multiple Output(MIMO)systems have massive antennas at base station.The high dimension of the channel makes it difficult for mobile users to accurately estimate downlink channel in real time.To address this issue,a weighted Orthogonal Matching Pursuit(OMP)algorithm is proposed in this paper.Firstly,the estimated signal calculated by the algorithm in each iteration is divided into two parts,the signal estimated from current residual signal and the signal estimated from previous residual signal.Secondly,these two parts of the signal are set with different weights to improve the estimation accuracy under low Signal Noise Ratio(SNR).Moreover,by adjusting the weight values with iterations,the estimation accuracy of the channel under both low and high SNR can be improved.The simulation results show that the proposed algorithm can obtain higher estimation accuracy than the standard OMP algorithm under different signal-to-noise ratios.

关 键 词：大规模多输入多输出(MIMO) 信道估计 稀疏重建 压缩感知 正交匹配追踪 

分 类 号：TN911[电子电信—通信与信息系统]