Adaptive minimum symbol-error-rate decision feedback equalization for multilevel pulse-amplitude modulation

The design of decision feedback equalizers (DFEs) is typically based on the minimum mean square error (MMSE) principle as this leads to effective adaptive implementation in the form of the least mean square algorithm. It is well-known, however, that in certain situations, the MMSE solution can be di...

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Bibliographic Details
Published in:IEEE transactions on signal processing Vol. 52; no. 7; pp. 2092 - 2101
Main Authors: Sheng Chen, Hanzo, L., Mulgrew, B.
Format: Journal Article
Language:English
Published: New York, NY IEEE 01.07.2004
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Adaptive algorithms
Adaptive equalizers
Algorithm design and analysis
Algorithms
Application software
Applied sciences
Computer simulation
Decision feedback equalizers
Detection, estimation, filtering, equalization, prediction
Equalization
Error analysis
Errors
Exact sciences and technology
Information, signal and communications theory
Least mean square algorithms
Least mean squares algorithm
Mathematical models
Mean square error methods
Multilevel
Probability density function
Pulse modulation
Signal and communications theory
Signal, noise
Symbols
Telecommunications and information theory
Performance evaluation
Adaptive algorithm
minimum mean square error
Decision feedback equalizers
Equalization
Stochastic method
Mean square error
Decision feedback equalizer
stochastic gradient adaptive algorithms
Simulation
minimum symbol error rate
Pulse amplitude modulation
Gradient method
Least mean squares methods
ISSN:1053-587X, 1941-0476
Online Access:Get full text
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Summary:The design of decision feedback equalizers (DFEs) is typically based on the minimum mean square error (MMSE) principle as this leads to effective adaptive implementation in the form of the least mean square algorithm. It is well-known, however, that in certain situations, the MMSE solution can be distinctly inferior to the optimal minimum symbol error rate (MSER) solution. We consider the MSER design for multilevel pulse-amplitude modulation. Block-data adaptive implementation of the theoretical MSER DFE solution is developed based on the Parzen window estimate of a probability density function. Furthermore, a sample-by-sample adaptive MSER algorithm, called the least symbol error rate (LSER), is derived for adaptive equalization applications. The proposed LSER algorithm has a complexity that increases linearly with the equalizer length. Computer simulation is employed to evaluate the proposed alternative MSER design for equalization application with multilevel signaling schemes.
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ISSN:1053-587X
1941-0476
DOI:10.1109/TSP.2004.828944