Blind Identification And Equalization For Multiple-input /multiple-output Channels - Global Telecommunications Conference, 1996. GLOBECOM '96. 'Communications: The Key to Global Prosp

AbstTactTo separa te and recover multiple signals in da t a communications, an tenna a r rays and acoustic sensor arrays, t h e impulse responses of multiple-input/multiple-output (MIMO) channels have t o b e identified explicitly or implicitly. This paper deals with t h e blind identification of MIMO F I R channels based on second-order statistics of t h e channel outpu ts and i ts application in blind channel equalization and signal separation. W e first investigate t h e identifiability of M I M O FIR channels, and obtain a necessary and sufficient condition for MIMO FIR channels t o be identifiable u p t o a unitary ambiguity matr ix using second-order statistics. Next, we extend the identification algorithms for single-input/multiple-output (SIMO) FIR channels, such as t h e algebraic algorithm and t h e subspace algorithm t o t h e identification of M I M O FIR channels. Since t h e ambiguity mat r ix can not be estimated using second-order statistics, we then present a forth-order cumulant based ambiguity matr ix estimation algorithm. Finally, we demonstrate effectiveness of t h e algorithms in this paper by computer simulations.