Blind System Identification Using Symbolic Dynamics

In this paper, a chaos-based approach is proposed for system identification with binary random signal. A chaos-based approach is developed to model random binary sequence and is applied to blind system identification. The Cramér Rao Lower Bound (CRLB)-based on the chaos representation is derived. The theoretical mean square error of the proposed approach is also derived. It is shown that the proposed blind approach achieves the CRLB asymptotically. The proposed technique is applied to blind channel equalization of a quadrature amplitude modulation communication system. The equalizer is based on expected maximization and unscented Kalman filtering and smoother. Our proposed method shows superior performance in comparison with conventional blind equalization techniques. The significance of this research is to extend the advantages of chaos to random signals for the blind system identification.