基于压缩感知的OFDM系统信道估计方法  

Channel Estimation Method of OFDM System based on Compressed Sensing

作　　者：李贵勇[1] 吕京昭 陈博 秦红 方泽圣 LI Gui-yong;LüJing-zhao;CHEN Bo;QIN Hong;FANG Ze-sheng(School of Communication and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,China)

机构地区：[1]重庆邮电大学通信与信息工程学院,重庆400065

出　　处：《光通信研究》2022年第1期52-57,共6页Study on Optical Communications

基　　金：国家科技重大专项资助项目(2017ZX03001021-004)。

摘　　要：针对无线信道的时域稀疏性以及稀疏度未知的问题,文章将压缩感知技术应用到正交频分复用(OFDM)系统信道估计中,提出了一种稀疏度自适应正交匹配追踪信道估计算法。算法利用离散傅里叶变换(DFT)信道估计算法对循环前缀内和外的噪声进行处理,估计得到的信道频率响应作为正交匹配追踪(OMP)算法稀疏迭代终止的判断条件,实现稀疏度自适应信号重建。同时在原子预选阶段,采用Dice系数准则代替内积准则作为相关性度量准则,可达到更优的估计性能。仿真结果表明,该算法相比于传统的压缩感知信道估计算法具有较好的性能,可以提高系统的归一化均方误差(NMSE)和误码率(BER)性能。Aiming at the time-domain sparsity and unknown sparsity of wireless channels,compressed sensing technology is applied to the channel estimation of Orthogonal Frequency Division Multiplexing(OFDM)system.This paper proposes a sparsity adaptive matching pursuit channel estimation algorithm.It uses the Discrete Fourier Transform(DFT)channel estimation algorithm to process the noise inside and outside the cyclic prefix.The estimated channel frequency response is used to terminate the sparse iteration of the Orthogonal Matching Pursuit(OMP)algorithm and realize the sparsity adaptive signal reconstruction.At the same time,in the atomic preselection stage,the Dice coefficient criterion is used instead of the inner product criterion as the correlation measurement criterion to achieve better estimation performance.The simulation results show that the algorithm has better performance than the traditional compressed sensing channel estimation algorithm,and can improve the system’s Normalized Mean Square Error(NMSE)and Bit Error Rate(BER)performance.

关 键 词：压缩感知 信道估计 稀疏度自适应 

分 类 号：TN929.5[电子电信—通信与信息系统]