基于压缩感知的MIMO-FBMC信道估计算法

Channel Estimation Algorithm Based on Compressive Sensing for MIMO-FBMC System

介绍编码的MIMO-FBMC系统,提出一种新的正则化稀疏自适应子空间追踪算法(RSASP),以提高最小二乘(LS)算法信道估计的精度,并设计了一种编码的RSASP算法用来估计MIMO-FBMC系统的信道频域响应(CFR)。算法分析和仿真结果表明,设计的编码RSASP算法与传统压缩采样匹配追踪(CoSaMP)和正则化正交匹配追踪(ROMP)算法相比,复杂度更低且需要观测的数据更少。此外,在双选择信道上,编码RSASP算法具有比OMP和ROMP算法更好的误码率(BER)性能。

The coded MIMO-FBMC system is introduced,a new regularized sparse adaptive subspace tracking algorithm(RSASP)is proposed,to improve the accuracy of the least squares(LS)algorithm channel estimation,and a coded RSASP algorithm is designed,to estimate the channel frequency response(CFR)of the MIMO-FBMC system.Algorithm analysis and simulation results show that the coding-RSASP algorithms can offer a low complexity and less measurements compared with conventional compressive sampling matching pursuit(CoSaMP)and regularized orthogonal matching pursuit(ROMP)methods.Moreover,the proposed coding-SASP algorithms have a better bit error ration(BER)performance than the conventional OMP and ROMP methods for MIMO-FBMC system in doubly selective channels.