MMSE estimation with CFAR detection for underwater communication channel

Various channel estimation methods have been proposed for shallow underwater communication channel with sparse channel type. A matching pursuit (MP), which is one of typical sparse channel estimation methods, can detect dominant components of sparse channel sequentially as a portion of matching. Mean squared error of MP, however, converges to fixed value even though signal-to-noise ratio (SNR) increases. This paper proposes a minimum mean squared error (MMSE) estimation method with constant false alarm (CFAR) detection for sparse channel estimation. Unlike MP, the mean squared error of the proposed method decreases as SNR increases and is lower than that of conventional MMSE estimators on the sparse channel. Experimental results show that the proposed method estimates sparse underwater communication channel efficiently.