Blind sequence detection of vector channels based on a novel clustering algorithm

Space diversity reception is known to be an excellent means of combating the detrimental effects of the mobile radio channel in data transmission. This paper addresses the problem of data detection for digital communications employing space diversity reception, where the system model contains a single input multiple output vector channel (this model may be further generalized to multiple-input multiple-output, MIMO vector channels). The received vector corrupted by AWGN is modeled as the noisy output of a finite state vector Markov source. Subsequently, a redundant discretely valued basis of minimal dimensionality is identified for the input space. Estimation of the output labels associated with these basis allows labeling of the state transition diagram. For this purpose, certain identifiable characteristics of the output sequences of the Markov source are used to classify its states and generate an initial codebook for a vector quantizer used to restore the output levels. Finally, an iterative implicit sequence detection algorithm is proposed for data detection.