Channel estimation based on distributed compressed sensing in amplify-and-forward relay networks

In orthogonal frequency-division multiplexing (OFDM) amplify-and-forward (AF) relay networks, in order to exploit diversity gains over frequency-selective fading channels, the receiver needs to acquire the knowledge of channel state information (CSI). In this article, based on the recent methodology of distributed compressed sensing (DCS), a novel channel estimation scheme is proposed. The joint sparsity model 2 (JSM-2) in DCS theory and simultaneous orthogonal matching pursuit (SOMP) are both introduced to improve the estimation performance and increase the spectral efficiency. Simulation results show that compared with current compressed sensing (CS) methods, the estimation error of our scheme is reduced dramatically in high SNR region while the pilot number is still kept small.