Generalized Yule-Walker Blind Identification for Single-Output Multiple-Output Systems

摘要

Blind identification for single-input multiple-output systems has received much attention in the areas of communication and signal processing. This paper extends the Yule-Walker identification method of auto-regressive models to single-input multiple-output systems and presents a generalized Yule-Walker blind identification algorithm. In order to increase the computational efficiency, the generalized Yule-Walker based recursive least squares blind identification algorithm is presented by using the recursive least squares principle. The simulation results show the effectiveness of the proposed algorithm.