Study on communication channel estimation by improved SOMP based on distributed compressed sensing

Abstract

Abstract Wireless communication channel usually show the feature of time-varying; however, the time-varying channel has the characteristic that the channel structure within the adjacent time slots having serious time correlation. Therefore, how to use the time slow-changing characteristics of the channel to design the suitable channel state information acquisition method is of great significance to further improve communication performance with low communication bit error rate (BER) for OFDM communication system. The distributed compressed sensing (DCS) is proposed for the phenomenon that multiple sparse signals with time correlation. Based on the DCS theory framework, this article will re-build a time-domain channel estimation method with joint structure by improving the synchronous orthogonal matching pursuit (simultaneous orthogonal matching pursuit, SOMP) algorithm to get better channel information acquisition performance. Simulation results demonstrate the effectiveness of the proposed channel estimation method. Compared with the conventional compressed sensing-based channel estimations which perform at each time separately, the method proposed has better performance in terms of BER.

Keywords

• Channel estimation
• Compressed sensing
• Joint sparse model
• Orthogonal frequency division multiplexing (OFDM)