Maximum likelihood sequence estimation
Maximum likelihood sequence estimation (MLSE) is a mathematical algorithm to extract useful data out of a noisy data stream.
Theory
For an optimized detector for digital signals the priority is not to reconstruct the transmitter signal, but it should do a best estimation of the transmitted data with the least possible amount of errors. The receiver emulates the distorted channel. All possible transmitted data streams are fed into this distorted channel model. The receiver compares the time response with the actual received signal and determines the most likely signal. E.g. root mean square deviation can be used as the decision criteria[1] for the lowest error probability.
References
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- ^ G. Bosco, P. Poggiolini, and M. Visintin, "Performance Analysis of MLSE Receivers Based on the Square-Root Metric," J. Lightwave Technol. 26, 2098-2109 (2008)
Further reading
- Andrea Goldsmith (2005). "Maximum Likelihood Sequence Estimation". Wireless Communications. pp. 362–364. ISBN 0521837162.
{{cite book}}: Unknown parameter|isnb13=ignored (help); Unknown parameter|pubisher=ignored (|publisher=suggested) (help) - Philip Golden, Hervé Dedieu, Krista Jacobsen, and Peter Reusens (2006). Fundamentals of DSL Technology. CRC Press. pp. 319–321. ISBN 0849319137.
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See also
- Maximum likelihood
- Maximum a posteriori (MAP) Estimation, which is more complex and requires a known distribution
External links
- W. Sauer-Greff, A. Dittrich, M. Lorang, and M. Siegrist (2001-04-16). "Maximum-Likelihood Sequence Estimation of Nonlinear Channels in High-Speed Optical Fiber Systems" (PDF). The Telecommunications Research Center Vienna.
{{cite web}}: Check date values in:|date=(help)CS1 maint: multiple names: authors list (link) - http://www.spec.gmu.edu/~pparis/classes/coll_732_1/node3.html
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