A MAP-based channel estimation algorithm for SIMO systems over extended SV channel model

In this paper, a maximum a posterior (MAP) based channel estimation algorithm is proposed to estimate both the temporal and spatial domain channel parameters for single-input multiple-output (SIMO) systems transmitting over an extended Saleh-Valenzuela (SV) channel. The proposed algorithm leverages on prior knowledge of the statistical distributions of signal clusters and rays within a cluster, and uses the expectation-maximization (EM) algorithm to resolve the high dimensional optimization problem into iteratively solving the multiple 3-dimensional optimizations. The successive interference cancellation (SIC) method is applied in the initialization stage to obtain the initial guess to the EM algorithm. Simulations are carried out in two typical indoor scenarios following the extended SV model. The proposed algorithm is shown to outperform the maximum likelihood (ML) based algorithm for SIMO systems.