Title :
Maximum likelihood sequence estimators: a geometric view
Author :
Barbosa, Lineu C.
Author_Institution :
IBM Almaden Res. Center, San Jose, CA, USA
fDate :
3/1/1989 12:00:00 AM
Abstract :
Communication issues are described in terms of macro operations between the data and the observation spaces. The problem of recovering the data is related to the inversion of an operator (the channel mapping); for this reason results available in linear algebra and functional analysis are applicable. Traditional concepts in communications are identified with these operations. An approach to the maximum-likelihood sequence estimator based on a sufficient statistic derived from these concepts is proposed. Intersymbol interference is removed by linear equalization, and a Viterbi-like dynamic programming algorithm takes into account the correlated noise in the metric evaluation. The performance of suboptimal receivers obtained by means of metric simplification is analyzed
Keywords :
estimation theory; filtering and prediction theory; information theory; intersymbol interference; MLSE; Viterbi-like dynamic programming algorithm; channel mapping; communications; correlated noise; functional analysis; geometric interpretation; information theory; intersymbol interference; linear algebra; linear equalization; matched filter; maximum-likelihood sequence estimator; metric evaluation; suboptimal receivers; Crosstalk; Dynamic programming; Equalizers; Functional analysis; Heuristic algorithms; Intersymbol interference; Linear algebra; Matched filters; Maximum likelihood estimation; Statistics;
Journal_Title :
Information Theory, IEEE Transactions on
