Modeling and simulation of MIMO-OFDM systems with classical and Bayesian channel estimation

Performance Analysis of Compressive Sensing based LS and MMSE Channel Estimation Algorithm

“…It is observed that classical channel estimation techniques such as LS and MMSE, together with multicarrier modulation systems can considerably enhance the system performance [7], [31]. Taking into account sparsity of the channel with only few significant channel coefficients, we can apply the compressive sensing theory in sparse channel estimation, thereby reducing the percentage of total channel coefficients sensed which in turn reduce the mathematical complexity and processing time required to recover all the channel coefficients.…”

“…of metrics like Bit Error Rate (BER) and Mean Square Error (MSE) is much better than LS channel estimation technique [6][7][8][9][10]. Based on the theory that the transmission channel is sparse with only few major channel coefficients, compressive sensing based channel estimation algorithms are also gaining popularity [11][12][13][14][15][16][17][18].…”