DocumentCode :
1359980
Title :
Decision feedback equaliser design using support vector machines
Author :
Chen, S. ; Gunn, S. ; Harris, C.J.
Author_Institution :
Dept. of Electron. & Comput. Sci., Southampton Univ., UK
Volume :
147
Issue :
3
fYear :
2000
fDate :
6/1/2000 12:00:00 AM
Firstpage :
213
Lastpage :
219
Abstract :
The conventional decision feedback equaliser (DFE) that employs a linear combination of channel observations and past decisions is considered. The design of this class of DFE is to construct a hyperplane that separates the different signal classes. It is well known that the popular minimum mean square error (MMSE) design is generally not the optimal minimum bit error rate (MBER) solution. A strategy is proposed for designing the DFE based on support vector machines (SVMs). The SVM design achieves asymptotically the MBER solution and is superior in performance to the usual MMSE solution. Unlike the exact MBER solution, this SVM solution can be computed very efficiently
Keywords :
adaptive equalisers; decision feedback equalisers; error statistics; learning systems; least mean squares methods; MBER solution; MMSE design; MMSE solution; adaptive equaliser; channel observations; decision feedback equaliser design; hyperplane; learning approach; linear-combiner DFE; minimum mean square error; optimal minimum bit error rate; past decisions; signal classes separation; support vector machines;
fLanguage :
English
Journal_Title :
Vision, Image and Signal Processing, IEE Proceedings -
Publisher :
iet
ISSN :
1350-245X
Type :
jour
DOI :
10.1049/ip-vis:20000360
Filename :
852302
Link To Document :
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