Sparse channel estimation for cyclic prefixed single carrier block transmission using compressed sensing

A sparse channel estimation method is proposed for cyclic prefixed single carrier block transmission with frequency domain equalization (CP-SCBT-FDE) system employed in sparse frequency selective fading channels by using compressed sensing (CS) technique. The sparse channel estimation in CP-SCBT-FDE system is formulated as a canonical CS problem, and a measurement matrix that satisfies restricted isometry property (RIP) is constructed to guarantee reliable channel impulse response (CIR) reconstruction from limited number of noisy observation measurements. Unlike the conventional channel estimation technique, such as frequency domain (FD) estimation and time domain (TD) least square (LS) estimation techniques, the new method can fully take the sparsity of the sparse frequency selective channel into account, which help improve the estimation accuracy of the sparse channel. Simulation results show that the proposed sparse channel estimation method outperforms the widely accepted TD and FD LS channel estimation methods in bit error rate (BER) and mean-square error (MSE).