Distributed Compressed Sensing-Based Channel Estimation and Pilot Allocation for MIMO Relay Networks

Distributed compressed sensing (DCS)-based channel estimation of multiple-input–multiple-output (MIMO) orthogonal frequency-division multiplexing for relay communication is considered in this paper. Specifically, the pilot allocation is addressed to optimize the channel estimation performance. Pilot placement in all the existing works based on Compressed Sensing (CS), address the mean square error (MSE) probabilistically via mutual coherence. On the contrary, we try to address the MSE of the estimate directly and optimize the MSE directly and design a pilot pattern to maximize the performance of the estimation. By taking into account the optimization approach, a combinatorial stochastic algorithm has been presented. Simulation results represent that the DCS-based MIMO relay channel estimation using optimized pilot placements will increase the performance from 3 to 10 dB as compared with the conventional least squares (LS) method. Moreover, the DCS-based MIMO relay channel estimation shows 2.3% and 45% improvement in spectrum efficiency under the same bit error rate performance over the compressed sensing (CS)-based channel estimation and traditional LS-based channel estimation approach, respectively.