Channel Estimation based on Compressive Sensing in OFDM Systems under Severely Fading Channels

Orthogonal Frequency Division Multiplexing (OFDM) is a digital multicarrier transmission technique which is based on Frequency division Multiplexing. Several multimedia standards uses Time Frequency Training Orthogonal Frequency Division Multiplexing (TFT-OFDM) as the key modulation technique. This paper introduces a high accurate, low complexity compressive sensing (CS) based channel estimation namely Auxiliary information based Subspace Pursuit (ASP) in TFT-OFDM systems. ASP based channel estimation in TFT-OFDM system is based on two steps. Firstly by using time domain training sequence (TS) path delay can be estimated. Then secondly by using a small amount of frequency domain pilots inserted into the OFDM data block channel can be perfectly estimated. Furthermore, the auxiliary information obtained in the first step is used to reduce complexity. Simulation results shows that proposed ASP algorithm has better performance than existing algorithm in both static and dynamic scenarios.