MAP sequence estimation for fading ISI channels.

In this paper we first describe a Maximum A Posterior (MAP) based sequence estimation approach for unknown, fast fading, frequency selective digital communications channels. The approach incorporates prior probabilistic knowledge of the channel via a stochastic channel model. We then assume a first order Gauss-Markov channel model to derive a specific MAP estimator, and we describe a Per Survivor Processing (PSP) algorithm as a realistic approximation of the optimum estimator. Monte Carlo simulations results are then presented: first to illustrate the performance realized when incorporating prior channel knowledge and its dependence on channel fading rate; and second to study the sensitivity of this MAP estimator to inaccuracies in the assumed values of parameters of the Gauss-Markov model.

Main Author: Chen, H.
Other Authors: Perry, R., Buckley, K.
Format: Villanova Faculty Authorship
Language: English
Published: 2001
Online Access: http://ezproxy.villanova.edu/login?url=https://digital.library.villanova.edu/Item/vudl:178435
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dc_source_str_mv March 2001 Conference on Information Sciences and Systems, March 2001, 1-5.
author Chen, H.
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Perry, R.
Buckley, K.
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Perry, R.
Buckley, K.
author_s Chen, H.
spellingShingle Chen, H.
MAP sequence estimation for fading ISI channels.
author-letter Chen, H.
author_sort_str Chen, H.
author2 Perry, R.
Buckley, K.
author2Str Perry, R.
Buckley, K.
dc_title_str MAP sequence estimation for fading ISI channels.
title MAP sequence estimation for fading ISI channels.
title_short MAP sequence estimation for fading ISI channels.
title_full MAP sequence estimation for fading ISI channels.
title_fullStr MAP sequence estimation for fading ISI channels.
title_full_unstemmed MAP sequence estimation for fading ISI channels.
collection_title_sort_str map sequence estimation for fading isi channels.
title_sort map sequence estimation for fading isi channels.
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description In this paper we first describe a Maximum A Posterior (MAP) based sequence estimation approach for unknown, fast fading, frequency selective digital communications channels. The approach incorporates prior probabilistic knowledge of the channel via a stochastic channel model. We then assume a first order Gauss-Markov channel model to derive a specific MAP estimator, and we describe a Per Survivor Processing (PSP) algorithm as a realistic approximation of the optimum estimator. Monte Carlo simulations results are then presented: first to illustrate the performance realized when incorporating prior channel knowledge and its dependence on channel fading rate; and second to study the sensitivity of this MAP estimator to inaccuracies in the assumed values of parameters of the Gauss-Markov model.
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dc.title MAP sequence estimation for fading ISI channels.
dc.creator Chen, H.
Perry, R.
Buckley, K.
dc.description In this paper we first describe a Maximum A Posterior (MAP) based sequence estimation approach for unknown, fast fading, frequency selective digital communications channels. The approach incorporates prior probabilistic knowledge of the channel via a stochastic channel model. We then assume a first order Gauss-Markov channel model to derive a specific MAP estimator, and we describe a Per Survivor Processing (PSP) algorithm as a realistic approximation of the optimum estimator. Monte Carlo simulations results are then presented: first to illustrate the performance realized when incorporating prior channel knowledge and its dependence on channel fading rate; and second to study the sensitivity of this MAP estimator to inaccuracies in the assumed values of parameters of the Gauss-Markov model.
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