Importance sampling simulation for evaluating the lower-bound BER of the Bayesian DFE
Importance sampling simulation for evaluating the lower-bound BER of the Bayesian DFE
We extend the importance sampling (IS) simulation technique of Iltis, originally derived for Bayesian equalizers, to evaluate the lower-bound bit error rate (BER) of the Bayesian decision feedback equalizer (DFE) under the assumption of correct decisions being fed back. Using a geometric translation approach, it is shown that the two subsets of opposite-class channel states are always linearly separable. A design procedure is presented, which chooses appropriate bias vectors for the simulation density to ensure asymptotic efficiency of the IS simulation.
179-182
Chen, S.
9310a111-f79a-48b8-98c7-383ca93cbb80
February 2002
Chen, S.
9310a111-f79a-48b8-98c7-383ca93cbb80
Chen, S.
(2002)
Importance sampling simulation for evaluating the lower-bound BER of the Bayesian DFE.
IEEE Transactions on Communications, 50 (2), .
Abstract
We extend the importance sampling (IS) simulation technique of Iltis, originally derived for Bayesian equalizers, to evaluate the lower-bound bit error rate (BER) of the Bayesian decision feedback equalizer (DFE) under the assumption of correct decisions being fed back. Using a geometric translation approach, it is shown that the two subsets of opposite-class channel states are always linearly separable. A design procedure is presented, which chooses appropriate bias vectors for the simulation density to ensure asymptotic efficiency of the IS simulation.
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Published date: February 2002
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submitted in July 1998, revised June 1999, accepted Aug. 2001
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Southampton Wireless Group
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Local EPrints ID: 251079
URI: http://eprints.soton.ac.uk/id/eprint/251079
PURE UUID: 7bccab40-14e8-4cf1-ab52-3223724f044a
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Date deposited: 13 Feb 2002
Last modified: 14 Mar 2024 05:08
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S. Chen
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