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• W2155449042 abstract "We apply the expectation-maximization Viterbi algorithm (EMVA) introduced in a previous paper to the blind or semi-blind maximum-likelihood equalization of continuous-phase modulated (CPM) signals transmitted over a noisy linear finite impulse response (FIR) channel. The EMVA is a computationally efficient technique for simultaneously performing system identification and signal detection whenever the transmission system admits a hidden Markov model (HMM) description. The convergence properties of the EMVA are examined and a method for monitoring the EMVA convergence rate online is presented. It is shown that the order of the FIR channel can be estimated by applying the order-incrementing (OI) and fixed-order (FO) methods proposed previously. A Cramer-Rao bound is derived for the channel impulse response, and it is shown via simulations that the EMVA approaches this bound as the SNR increases. Finally, an EMVA-based technique is described for estimating the error covariance matrix for the system parameters for the case of long observation blocks." @default.
• W2155449042 created "2016-06-24" @default.
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• W2155449042 date "2003-10-01" @default.
• W2155449042 modified "2023-09-23" @default.
• W2155449042 title "Blind and semi-blind equalization of CPM signals with the EMV algorithm" @default.
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• W2155449042 doi "https://doi.org/10.1109/tsp.2003.816876" @default.
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