Title :
On MLSE algorithms for unknown fast time-varying channels
Author :
Chen, Hai ; Perry, Richard ; Buckley, Kevin
Author_Institution :
Electr. & Comput. Eng. Dept., Villanova Univ., PA, USA
fDate :
5/1/2003 12:00:00 AM
Abstract :
We consider maximum-likelihood sequence estimation (MLSE) algorithms for unknown, time-varying intersymbol interference communication channels. We assume a statistical channel model, and marginalize over model parameters to derive expectation-maximization (EM) algorithms for both time-independent Gaussian and Gauss-Markov models, and we contrast these with direct MLSE and computationally efficient per-survivor processing implementations. We identify a general concern associated with the convergence of EM-based discrete parameter (e.g., symbol) estimators.
Keywords :
Gaussian channels; Gaussian processes; Markov processes; channel estimation; convergence of numerical methods; intersymbol interference; maximum likelihood estimation; maximum likelihood sequence estimation; optimisation; statistical analysis; time-varying channels; EM-based discrete parameter convergence; Gaussian channels; ISI channels; MLSE algorithms; computationally efficient per-survivor processing; expectation-maximization algorithms; fast time-varying channels; intersymbol interference; list Viterbi algorithm; maximum-likelihood sequence estimation; model parameters; optimum Viterbi algorithm; statistical channel model; symbol estimators; time-independent Gauss-Markov models; time-independent Gaussian models; Convergence; Gaussian channels; Intersymbol interference; Iterative algorithms; Maximum likelihood detection; Maximum likelihood estimation; Parameter estimation; Signal processing algorithms; Time-varying channels; Viterbi algorithm;
Journal_Title :
Communications, IEEE Transactions on
DOI :
10.1109/TCOMM.2003.811381
