Compressed Sensing Based Channel Estimation for OFDM Transmission under 3GPP Channels

A large number of pilots are utilized to acquire channel information in traditional channel estimation for Orthogonal Frequency Division Multiplexing (OFDM) system, which leads to lower spectrum efficiency. For exploiting the sparse channel characteristics of 3GPP multipath channels, we employ the Compressed Sensing (CS) approach for channel estimation. Two CS-based recovery algorithms, Orthogonal matching pursuit (OMP) algorithm and Compressive sampling matching pursuit (CoSaMP) algorithm, are considered in this paper. The Bit error rate (BER) and Mean squared error (MSE) performance using traditional least square(LS), and two CS-based algorithms are given. Simulation results demonstrate that the CoSaMP algorithm achieves best performance with fewer pilots among three algorithms under 3GPP channels.