Blind identification and equalization for wireless communications using antenna arrays

Antenna arrays can be used in wireless communication systems to increase system capacity and improve communication quality. The antenna arrays, which receive several signals at the same time and frequency domain, can be modeled as a multiple-input/multiple-output (MIMO) system. To separate and recover multiple signals from arrays, the parameters of the system have to be identified explicitly or implicitly. In the first part of this paper, we deals with blind parameter identification based on second-order statistics. We investigate the identifiability of the MIMO FIR channels, and obtain a necessary and sufficient condition for second-order based identifiability of the MIMO FIR channels. Then, we extend the identification algorithms for single-input/multiple-output (FIR-SIMO) channels, such as the algebraic algorithm and the subspace algorithms to the identification of the MIMO FIR channels. The MIMO systems can also be directly equalized using blind techniques. We then investigate blind algorithms to separate multiple signals received by antenna arrays. We analyze the CMA equalizer used in the MIMO systems. According to our analysis, for the MIMO FIR, channels satisfying certain conditions, the MIMO-CMA FIR equalizer is able to recover one of input signals and remove the intersymbol interference and co-channel interference regardless of the initial setting of the equalizer. To recover all input signals simultaneously, a novel MIMO channel blind equalization algorithm is developed in this paper. The global convergence of the new algorithm for MIMO channels is proved. Hence, the new blind equalization algorithm for MIMO channels can be applied to separate and equalize the signals received by antenna arrays in communication systems.