Abstract
This paper deals with blind deconvolution for signal recovery in multipath multiple-input multiple-output (MIMO) systems, where the delays of different paths of each source signal from transmit antenna to receive antenna are random. Such a problem is often solved in an ideal state in literature, i.e., each transmitted signal arrives at the receive antennas simultaneously and the arrival time intervals of two adjacent paths are identical. However, the ideal case could not be satisfied in most applications. To address this issue, we propose a blind signal recovery algorithm. Specifically, by using Taylor series expansion to approximate sources, the convolutive MIMO signal recovery problem is transferred into instantaneous blind source separation (BSS) problem. Building on the ideas of second-order blind identification (SOBI), an extended SOBI algorithm is developed to recover the extended sources (including original sources and their derivatives). The simulation results illustrate the well performance and the interest of the proposed algorithm in comparison with other approaches.
An adaptive super-exponential deflation algorithm for blind deconvolution of MIMO systems using the QR-factorization of matrix algebra
