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