A Data-Bearing Approach for Pilot-Embedding Frameworks in Space-Time Coded MIMO Systems
Space-time (ST) coded MIMO systems employing coherent detectors crucially require channel state information. This paper presents a novel pilot-embedding framework for channel estimation and data detection by exploiting the null-space property and the orthogonality property of the data-bearer and pilot matrices. The ST data matrix is firstly projected onto the data bearer matrix, which is a null-space of the pilot matrix, and the resulting matrix and the pilot matrix are combined for transmitting. The data and pilot extractions are achieved independently through linear transformations by exploiting the null-space property. The unconstrained maximum-likelihood (ML) and linear minimum mean-squared error (lmmse) estimators are explored for channel estimation. Then the ML approach for data detection is developed by exploiting the orthogonality property. The mean-squared error (mse) of channel estimation, Cramer-Rao lower bound (CRLB), and the Chernoff's bound of a pair-wise error probability for ST codes are analyzed for examining the performance of the proposed scheme. The optimum power allocation scheme for data and pilot parts is also considered. Three data-bearer and pilot structures, including time-multiplexing (TM)-based, ST-block-code (STBC)-based, and code-multiplexing (CM)-based, are proposed. Simulation results show that the CM-based structure provides superior performance for nonquasi-static flat Rayleigh fading channels, while these three structures yield similar performances for quasi-static flat Rayleigh fading channels