Compressed Channel Sensing for Two-way Relay Network

Two-way relay network (TWRN) was introduced to realize high-data rate transmission and to improve spatial diversity over the frequency-selective fading channel. However, channel state information (CSI) is needed due to the requirement from coherent data detection and the self-data removal at terminals. Traditional training-based linear probing techniques are able to achieve the accurate CSI by using enough training sequence. However, these methods may lead to a low efficiency on the bandwidth due to that based on the implicit assumption of a rich underlying multipath, while neglected inherent channel sparsity in the TWRN. Unlike the previous methods, we propose a compressed channel sensing method (sometimes be called compressed sensing–based sparse channel estimation method) which exploits the sparse structure, and hence provide significant improvements in MSE performance when compared with conventional LS-based linear channel probing strategies in the TWRN. Simulation results confirm performance of the proposed method. Keyword Compressed channel sensing (CCS), two-way relay network (TWRN), sparse channel estimation, Restricted Isometry Property (RIP).