A novel effective compressed sensing based sparse channel estimation in OFDM system

The optimal tradeoff among the channel estimation performance, spectrum efficiency and computational complexity has always been one of the major topics for wireless communication system especially OFDM system. Traditional channel estimation methods are usually based on the classical (Least Squares) LS method without considering whether the multipath channel is sparse or rich, therefore, those methods can hardly balance the channel estimation performance, spectrum efficiency and computational complexity. In this paper, we propose an effective compressed sensing (CS) based sparse channel estimation method for OFDM system. As an efficient reconstruction tool for CS, the orthogonal matching pursuit (OMP) is adopted in this paper for sparse channel estimation. For OMP algorithm, an good threshold is essential to promote the channel estimation accuracy. The proposed threshold is formulated based on theoretical derivation and analysis. Both simulation results and computational complexity evaluation show that the proposed method can effectively balance the channel estimation performance, spectrum efficiency and computational complexity.