Structured Compression-sensing Method for MIMO-OFDM in ITU_VB and DVB_T2 channels

Structured Compression Sensing (SCS) is a relatively new subject that has piqued the curiosity of wireless communication systems. The time-frequency joint channel estimation, which is dissimilar to the usual channel evaluation scheme, is used in this study to offer a structured compression sensing technique during a multi-input and multi-output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) structure. A Priori Information Assisted Adaptive Structured Subspace Pursuit algorithm (PAASSP) is carried out and the comparison is done between them for SNR, MSE, and BER. This algorithm is carried out by using a 4×4 MIMO OFDM system. The channel coefficients are obtained for PA-ASSP using Time-Frequency Training (TFT) based channel evaluation. These algorithms are analyzed and simulated for inputs parameters like a 4×4 antenna system, pilots, and several subcarriers. The simulation is carried out using MATLAB and the outcome exhibits that the suggested practices can approximate the channel more precisely with smaller amount pilots, and after SNR go beyond 20db the MSE routine decreases twice the previous value showing better performance. Also, the outcome is nearly identical for both standard DVB-T2 and ITU_VB channels.