An EM-Based Forward-Backward Kalman Filter for the Estimation of Time-Variant Channels in OFDM

Orthogonal frequency division multiplexing (OFDM) combines the advantages of high achievable rates and relatively easy implementation. However, for proper recovery of the input, the OFDM receiver needs accurate channel information. In this paper, we propose an expectation-maximization algorithm for...

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Main Author: Al-Naffouri, T.Y. (author)
Other Authors: unknown (author)
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Published: 0000
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Online Access:https://eprints.kfupm.edu.sa/id/eprint/14261/1/14261_1.pdf
https://eprints.kfupm.edu.sa/id/eprint/14261/2/14261_2.doc
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author Al-Naffouri, T.Y.
author2 unknown
author2_role author
author_facet Al-Naffouri, T.Y.
unknown
author_role author
dc.creator.none.fl_str_mv Al-Naffouri, T.Y.
unknown
dc.date.none.fl_str_mv 0000-07
2020
dc.format.none.fl_str_mv application/pdf
application/msword
dc.identifier.none.fl_str_mv https://eprints.kfupm.edu.sa/id/eprint/14261/1/14261_1.pdf
https://eprints.kfupm.edu.sa/id/eprint/14261/2/14261_2.doc
(0000) An EM-Based Forward-Backward Kalman Filter for the Estimation of Time-Variant Channels in OFDM. Signal Processing, IEEE Transactions on [see also Acoustics, Speech, and Signal Processing, IEEE Transactions on], 55.
dc.language.none.fl_str_mv en
en
dc.publisher.none.fl_str_mv IEEE
dc.relation.none.fl_str_mv https://eprints.kfupm.edu.sa/id/eprint/14261/
dc.rights.*.fl_str_mv info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Computer
dc.title.none.fl_str_mv An EM-Based Forward-Backward Kalman Filter for the Estimation of Time-Variant Channels in OFDM
dc.type.none.fl_str_mv Article
PeerReviewed
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article
description Orthogonal frequency division multiplexing (OFDM) combines the advantages of high achievable rates and relatively easy implementation. However, for proper recovery of the input, the OFDM receiver needs accurate channel information. In this paper, we propose an expectation-maximization algorithm for joint channel and data recovery in fast fading environments. The algorithm makes a collective use of the data and channel constraints inherent in the communication problem. This comes in contrast to other works which have employed these constraints selectively. The data constraints include pilots, the cyclic prefix, and the finite alphabet restriction, while the channel constraints include sparsity, finite delay spread, and the statistical properties of the channel (frequency and time correlation). The algorithm boils down to a forward-backward Kalman filter. We also suggest a suboptimal modification that is able to track the channel and recover the data with no latency. Simulations show the favorable behavior of both algorithms compared to other channel estimation techniques.
eu_rights_str_mv openAccess
format article
id KFUPM_4c1625b85405b3e2daf0017f8d9ac12d
identifier_str_mv (0000) An EM-Based Forward-Backward Kalman Filter for the Estimation of Time-Variant Channels in OFDM. Signal Processing, IEEE Transactions on [see also Acoustics, Speech, and Signal Processing, IEEE Transactions on], 55.
language_invalid_str_mv en
network_acronym_str KFUPM
network_name_str King Fahd University of Petroleum and Minerals
oai_identifier_str oai::14261
publishDate 0000
publisher.none.fl_str_mv IEEE
repository.mail.fl_str_mv
repository.name.fl_str_mv
repository_id_str
spelling An EM-Based Forward-Backward Kalman Filter for the Estimation of Time-Variant Channels in OFDMAl-Naffouri, T.Y.unknownComputerOrthogonal frequency division multiplexing (OFDM) combines the advantages of high achievable rates and relatively easy implementation. However, for proper recovery of the input, the OFDM receiver needs accurate channel information. In this paper, we propose an expectation-maximization algorithm for joint channel and data recovery in fast fading environments. The algorithm makes a collective use of the data and channel constraints inherent in the communication problem. This comes in contrast to other works which have employed these constraints selectively. The data constraints include pilots, the cyclic prefix, and the finite alphabet restriction, while the channel constraints include sparsity, finite delay spread, and the statistical properties of the channel (frequency and time correlation). The algorithm boils down to a forward-backward Kalman filter. We also suggest a suboptimal modification that is able to track the channel and recover the data with no latency. Simulations show the favorable behavior of both algorithms compared to other channel estimation techniques.IEEE0000-072020ArticlePeerReviewedinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfapplication/mswordhttps://eprints.kfupm.edu.sa/id/eprint/14261/1/14261_1.pdfhttps://eprints.kfupm.edu.sa/id/eprint/14261/2/14261_2.doc (0000) An EM-Based Forward-Backward Kalman Filter for the Estimation of Time-Variant Channels in OFDM. Signal Processing, IEEE Transactions on [see also Acoustics, Speech, and Signal Processing, IEEE Transactions on], 55. enenhttps://eprints.kfupm.edu.sa/id/eprint/14261/info:eu-repo/semantics/openAccessoai::142612019-11-01T14:05:00Z
spellingShingle An EM-Based Forward-Backward Kalman Filter for the Estimation of Time-Variant Channels in OFDM
Al-Naffouri, T.Y.
Computer
status_str publishedVersion
title An EM-Based Forward-Backward Kalman Filter for the Estimation of Time-Variant Channels in OFDM
title_full An EM-Based Forward-Backward Kalman Filter for the Estimation of Time-Variant Channels in OFDM
title_fullStr An EM-Based Forward-Backward Kalman Filter for the Estimation of Time-Variant Channels in OFDM
title_full_unstemmed An EM-Based Forward-Backward Kalman Filter for the Estimation of Time-Variant Channels in OFDM
title_short An EM-Based Forward-Backward Kalman Filter for the Estimation of Time-Variant Channels in OFDM
title_sort An EM-Based Forward-Backward Kalman Filter for the Estimation of Time-Variant Channels in OFDM
topic Computer
url https://eprints.kfupm.edu.sa/id/eprint/14261/1/14261_1.pdf
https://eprints.kfupm.edu.sa/id/eprint/14261/2/14261_2.doc