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Decision feedback equalizer design using support vector machines

Decision feedback equalizer design using support vector machines
Decision feedback equalizer design using support vector machines
We consider the conventional decision feedback equalizer (DFE) that employs a linear combination of the channel observations and the past decisions. 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. We propose a strategy for designing the DFE based on support vector machines (SVM). 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 much more efficiently.
213-219
Chen, S.
ac405529-3375-471a-8257-bda5c0d10e53
Gunn, S.R.
306af9b3-a7fa-4381-baf9-5d6a6ec89868
Harris, C.J.
c4fd3763-7b3f-4db1-9ca3-5501080f797a
Chen, S.
ac405529-3375-471a-8257-bda5c0d10e53
Gunn, S.R.
306af9b3-a7fa-4381-baf9-5d6a6ec89868
Harris, C.J.
c4fd3763-7b3f-4db1-9ca3-5501080f797a

Chen, S., Gunn, S.R. and Harris, C.J. (2000) Decision feedback equalizer design using support vector machines. IEE Proceedings - Vision, Image and Signal Processing, 147 (3), 213-219.

Record type: Article

Abstract

We consider the conventional decision feedback equalizer (DFE) that employs a linear combination of the channel observations and the past decisions. 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. We propose a strategy for designing the DFE based on support vector machines (SVM). 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 much more efficiently.

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More information

Published date: June 2000
Organisations: Electronic & Software Systems, Southampton Wireless Group

Identifiers

Local EPrints ID: 251073
URI: https://eprints.soton.ac.uk/id/eprint/251073
PURE UUID: 0f609165-913b-4c59-994a-a323d93bc10b

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Date deposited: 29 Oct 2001
Last modified: 24 Jul 2017 16:42

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Contributors

Author: S. Chen
Author: S.R. Gunn
Author: C.J. Harris

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