A Novel Wide Band HF Channel Estimation Algorithm Based on Compressed Sensing in OFDM System

摘要

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 and spectrum efficiency. In this paper, we propose a Sparsity Adaptive Orthogonal Matching Pursuit algorithm (SAOMP), which is an effective Compressed Sensing (CS) based short wave (HF) channel estimation algorithm for OFDM system. Simulation results show that the proposed method can effectively balance the channel estimation performance and spectrum efficiency without knowing the channel sparse degree.