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Asymptotic Bayesian Decision Feedback Equalizer Using a Set of Hyperplanes

Chen, S., Mulgrew, B. and Hanzo, L. (2000) Asymptotic Bayesian Decision Feedback Equalizer Using a Set of Hyperplanes IEEE Transactions on Signal Processing, 48, (12), pp. 3493-3500.

Record type: Article

Abstract

We present a signal space partitioning technique for realizing the optimal Bayesian decision feedback equalizer (DFE). It is known that, when the signal to noise ratio (SNR) tends to infinity, the decision boundary of the Bayesian DFE is asymptotically piecewise linear and consists of several hyperplanes. The proposed technique determines these hyperplanes explicitly and uses them to partition the observation signal space. The resulting equalizer is made up of a set of parallel linear discriminant functions and a Boolean mapper. Unlike the existing signal space partitioning technique of Kim and Moon, which involves complex combinatorial search and optimization in design, our design procedure is simple and straightforward, and guarantees to achieve the asymptotic Bayesian DFE.

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Published date: December 2000
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 251151
URI: http://eprints.soton.ac.uk/id/eprint/251151
ISSN: 1053-587X
PURE UUID: 1be729ea-0e26-4cde-9ede-44d386b0c71d

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Date deposited: 12 Jan 2004
Last modified: 18 Jul 2017 10:11

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Contributors

Author: S. Chen
Author: B. Mulgrew
Author: L. Hanzo

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