Sparse Channel Estimation for Dual-Hop Amplify-and-Forward Cooperative Communiacion Systems

Abstract

Cooperative transmission is one of key techniques which can improve system capacity and transmit range with limit power in the next-generation communication systems. However, accurate Channel State Information (CSI) is necessary at the destination for coherent detection. Consider a Dual-Hop Amplify-and-Forward (DHAF) Cooperative Communication System (CCS), traditional linear channel estimation method, e.g., Least Square (LS), based assumption of the rich multipath cascaded channel, is robust and simple while at the cost of low spectrum efficiency. Recent channel measurements have shown that the wireless channel exhibits great sparse in some high- dimensional space. In this study, we confirmed that cascaded channel exhibits sparse distribution if the two individual channels are sparse by using representative simulation results. Later, we propose an efficient sparse channel estimation method to take advantage of the inherent sparse prior information in DHAF CCS. Simulation results confirm the superiority of our proposed methods over LS-based linear channel estimation method.