改进加权匹配追踪信道估计算法  

Improved Weighted Matching Pursuit based Channel Estimation Algorithm

作　　者：吕治国[1] 齐萌[1] 邵鸿翔[1] LüZhi-guo;QI Meng;SHAO Hong-xiang(School of Computer and Information Engineering,Luoyang Institute of Science and Technology,Luoyang 471023,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

出　　处：《光通信研究》2022年第1期63-66,77,共5页Study on Optical Communications

基　　金：河南省自然科学基金资助项目(202300410286);河南省科技攻关资助项目(192102210249,192102210116,212102210470);河南省高等学校重点资助项目(19A520006,19B510007)。

摘　　要：基于压缩感知的匹配追踪算法可以用较短导频序列估计大规模天线通信系统稀疏信道,具有计算复杂度低,需要导频数量少的优点,但信道估计精度不高。依据估计误差大小给各次迭代获得的信道估计值加权,能在低信噪比(SNR)条件下提高估计精度,但会降低高SNR条件下的估计精度。为了解决这个问题,文章提出了一种改进的加权匹配追踪算法。先通过对信道数据训练获取权值信息,然后随迭代次数自适应调整权值,从而改善估计精度性能。仿真结果表明,改进算法在保证低SNR估计精度前提下,改善了高SNR条件下的估计精度性能。Compressive sensing based matching pursuit algorithm can estimate the channel state information of communication system with shorter pilot sequences.It has the advantages of lower computational complexity and less number of pilots.However,the estimation accuracy is relatively low.Assigning different weights to the estimated channel according to the estimation error can improve the estimation performance under low Signal Noise Ratio(SNR)conditions.Nevertheless,it will reduce the estimation accuracy under high SNR conditions.To address this issue,an improved weighted matching pursuit algorithm is proposed.The information of weight value is obtained by training the channel data.Adjusting the weight values adaptively with the iterations can further improve the estimation accuracy.The simulation results show that the proposed algorithm can improve the estimation performance under both low and high SNR conditions.

关 键 词：大规模天线 压缩感知 匹配追踪 稀疏重建 信道估计 

分 类 号：TN911[电子电信—通信与信息系统]