基于分布式压缩感知的改进SOMP信道估计算法

针对多径信道联合稀疏模型，基于分布式压缩感知理论提出了一种适用于正交频分复用（Orthogonal Frequency Division Multiplexing，OFDM）通信系统的改进同时正交匹配追踪（Simultaneous Orthogonal Matching Pursuit，SOMP）信道估计算法。该算法首先联合多个符号利用比较残差和的方式，在每次迭代中估计各符号信道响应公共支撑集与相应元素直到公共支撑集估计结束，然后对各符号信道响应非公共支撑集单独进行估计，最终得到多个符号的信道响应估计值。仿真结果表明，改进的SOMP算法在JSM-2模型下性能与传统的SOMP算法相近，在JSM-1模型下性能优于传统的SOMP算法与OMP算法。

An improved SOMP channel estimation algorithm based on distributed compressed sensing

For multipath channel joint sparse model,an improved simultaneous orthogonal matching pursuit(SOMP) channel estimation algorithm suitable for orthogonal frequency division multiplexing(OFDM) communication system is proposed based on distributed compressed sensing.The algorithm first combines multiple symbols and compares the residual sum.In each iteration,it estimates the common support set and corresponding elements of each symbol channel response until the end of the common support set estimation,and then the channel response of each symbol is estimated separately from the non-common support set,finally channel response estimates of multiple symbols are obtained.The simulation results show that the performance of the improved SOMP algorithm under the JSM-2 model is similar to that of the traditional SOMP algorithm,and the performance under the JSM-1 model is better than that of the traditional SOMP algorithm and OMP algorithm.