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Adaptive minimum-BER decision feedback equalisers for binary signalling

Adaptive minimum-BER decision feedback equalisers for binary signalling
Adaptive minimum-BER decision feedback equalisers for binary signalling
The problem of constructing adaptive minimum bit error rate (MBER) decision feedback equalisers (DFEs) for binary signalling is considered. Gradient and Gauss}Newton algorithms are considered for both conventional and state (or
space) translation forms of the DFE. The Hessian matrix for the Gauss}Newton algorithm is introduced for the first time. Kernel density estimation is demonstrated to provide a convenient mechanism for approximating the BER as a smooth function of the available data. This leads to the development of a number of block and serial adaptive algorithms. Computer simulation is used to assess the performance of these algorithms.
0165-1684
1479-1489
Mulgrew, B.
95a3fbda-7de2-4583-b1f2-0a54a69b414a
Chen, S.
9310a111-f79a-48b8-98c7-383ca93cbb80
Mulgrew, B.
95a3fbda-7de2-4583-b1f2-0a54a69b414a
Chen, S.
9310a111-f79a-48b8-98c7-383ca93cbb80

Mulgrew, B. and Chen, S. (2001) Adaptive minimum-BER decision feedback equalisers for binary signalling. Signal Processing, 81 (7), 1479-1489.

Record type: Article

Abstract

The problem of constructing adaptive minimum bit error rate (MBER) decision feedback equalisers (DFEs) for binary signalling is considered. Gradient and Gauss}Newton algorithms are considered for both conventional and state (or
space) translation forms of the DFE. The Hessian matrix for the Gauss}Newton algorithm is introduced for the first time. Kernel density estimation is demonstrated to provide a convenient mechanism for approximating the BER as a smooth function of the available data. This leads to the development of a number of block and serial adaptive algorithms. Computer simulation is used to assess the performance of these algorithms.

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More information

Published date: July 2001
Additional Information: submitted for publication in Oct. 1999, revised in July 2000 and accepted in Feb. 2001
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 251153
URI: http://eprints.soton.ac.uk/id/eprint/251153
ISSN: 0165-1684
PURE UUID: 86f7c645-eb58-4ca8-ba7f-cc5f766dab93

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Date deposited: 29 Aug 2001
Last modified: 14 Mar 2024 05:10

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Contributors

Author: B. Mulgrew
Author: S. Chen

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