Mimo-OFDM Compressed Channel Estimation Using Forward-Backward Pursuit

Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO-OFDM) channel estimation is considered recently utilizing Compressed Sensing (CS) based methods. Here, we proposed to use the joint sparsity of MIMO-OFDM channels using Forward Backward Pursuit (FBP) algorithm. In order to increase the accuracy of estimation, we proposed to take into account the common sparsity of MIMO channels in each step and to exploit common sparsity in the system model. Furthermore, the backward steps improve the accuracy by omitting evil previously gathered atoms. Simulation results represent the superiority of the proposed FBP-based channel estimation approach rather than the conventional CS-based approaches.