Importance sampling simulation for evaluating the lower-bound BER of the Bayesian DFE

by: Sheng Chen

Communications, IEEE Transactions on, Vol. 50, No. 2. (2002), pp. 179-182.

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Abstract

An importance sampling (IS) simulation technique, originally derived by Iltis (1995) for Bayesian equalizers, is extended to evaluate the lower-bound bit error rate of the Bayesian decision feedback equalizer (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

@article{citeulike:1911400, abstract = {An importance sampling (IS) simulation technique, originally derived by Iltis (1995) for Bayesian equalizers, is extended to evaluate the lower-bound bit error rate of the Bayesian decision feedback equalizer (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}, author = {Chen, Sheng }, booktitle = {Communications, IEEE Transactions on}, citeulike-article-id = {1911400}, journal = {Communications, IEEE Transactions on}, keywords = {importance, sampling}, number = {2}, pages = {179--182}, posted-at = {2007-11-13 23:46:15}, priority = {2}, title = {Importance sampling simulation for evaluating the lower-bound BER of the Bayesian DFE}, url = {http://ieeexplore.ieee.org/xpls/abs\_all.jsp?arnumber=983311}, volume = {50}, year = {2002} }

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TY - JOUR ID - citeulike:1911400 L3 - citeulike-article-id:1911400 TI - Importance sampling simulation for evaluating the lower-bound BER of the Bayesian DFE T2 - Communications, IEEE Transactions on JF - Communications, IEEE Transactions on VL - 50 IS - 2 SP - 179 EP - 182 N2 - An importance sampling (IS) simulation technique, originally derived by Iltis (1995) for Bayesian equalizers, is extended to evaluate the lower-bound bit error rate of the Bayesian decision feedback equalizer (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 KW - importance KW - sampling AU - Chen, Sheng PY - 2002/// UR - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=983311 ER -

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