Threshold based most significant taps detection for sparse channel estimation in OFDM system

This paper addresses the effective sparse channel estimation based on the most significant taps (MST) selection with high spectral efficiency and moderate computational complexity for orthogonal frequency division multiplexing (OFDM) systems. The main goal of this paper is to obtain an efficient time domain threshold and achieve the channel estimation performance approaching the least squares (LS) method with exact sparsity (exact number of non-zero channel taps) without using prior knowledge of both channel statistics and noise standard deviation. Firstly, classical LS method is used to get an initial channel impulse response (CIR) estimate. Then a novel effective threshold, estimated from the noise coefficients of the initial estimated CIR, is proposed. Finally, the obtained threshold is used to select the most significant taps. Simulations show that the proposed method is able to achieve good channel estimation performances for sparse channel within a comparatively wide range of sparsity with small number of pilots and moderate computational complexity.