In this paper, the base-band signal collected from an unknown, multipath, multi-receiver FIR channel is viewed as a state sequence generated by a hidden Mrkov model whose state and order are unkown and whose transition probability matrix is known once the ordr is given. Based on this view, two types of algorithms are developd for acquisition and tracking, rspectively. The algorithms are sutitable for both block and non-block transmissions, and for time-varying channels. For acquistion, the states and the transition probability matrix of fully-connected HMM with a possible lower order are extimated y usnig a clustering algorthm. Then a state sequence is estimate based on a maximum a posterior estimator using the Viterbi algorithm iwth a fully co=nnected trellis. In tracking, the symbol sequence is estimated by the Viterbi algorithm, and the states of the HMM are updated at each release of estimated states. Simulation result shows that the proposed blind algorithms with the lower-ordered HMM achieve the BER with only 1 dB degradation in SNR compared with the ML estimator utilizing the known channel parameters. This confirms theoretical analysis.
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