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Article: Symbol timing estimation in MIMO correlated flat-fading channels

TitleSymbol timing estimation in MIMO correlated flat-fading channels
Authors
KeywordsCramer-Rao Bound
Data-Aided
Maximum Likelihood
Mimo, Correlated Fading
Non-Data Aided
Optimal Training Sequences
Symbol Timing Estimation
Issue Date2004
PublisherJohn Wiley & Sons Ltd. The Journal's web site is located at http://www3.interscience.wiley.com/cgi-bin/jhome/76507157
Citation
Wireless Communications And Mobile Computing, 2004, v. 4 n. 7, p. 773-790 How to Cite?
AbstractIn this paper, the data aided (DA) and non-data aided (NDA) maximum likelihood (ML) symbol timing estimators and their corresponding conditional Cramer-Rao bound (CCRB) and modified Cramer-Rao bound (MCRB) in multiple-input-multiple-output (MIMO) correlated flat-fading channels are derived. It is shown that the approximated ML algorithm in References [4,13] is just a special case of the DA ML estimator; while the extended squaring algorithm in Reference [14] is just a special case of the NDA ML estimator. For the DA case, the optimal orthogonal training sequences are also derived. It is found that the optimal orthogonal sequences resemble the Walsh sequences, but present different envelopes. Simulation results under different operating conditions (e.g. number of antennas and correlation between antennas) are given to assess and compare the performances of the DA and NDA ML estimators with respect to their corresponding CCRBs and MCRBs. It is found that (i) the mean square error (MSB) of the DA ML estimator is close to the CCRB and MCRB, (ii) the MSB of the NDA ML estimator is close to the CCRB but not to the MCRB, (iii) the MSEs of both DA and NDA ML estimators are approximately independent of the number of transmit antennas and are inversely proportional to the number of receive antennas, (iv) correlation between antennas has little effect on the MSEs of DA and NDA ML estimators and (v) DA ML estimator performs better than NDA ML estimator at the cost of lower transmission efficiency and higher implementation complexity. Copyright © 2004 John Wiley & Sons, Ltd.
Persistent Identifierhttp://hdl.handle.net/10722/155251
ISSN
2015 Impact Factor: 0.922
2015 SCImago Journal Rankings: 0.421
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorWu, YCen_US
dc.contributor.authorSerpedin, Een_US
dc.date.accessioned2012-08-08T08:32:33Z-
dc.date.available2012-08-08T08:32:33Z-
dc.date.issued2004en_US
dc.identifier.citationWireless Communications And Mobile Computing, 2004, v. 4 n. 7, p. 773-790en_US
dc.identifier.issn1530-8669en_US
dc.identifier.urihttp://hdl.handle.net/10722/155251-
dc.description.abstractIn this paper, the data aided (DA) and non-data aided (NDA) maximum likelihood (ML) symbol timing estimators and their corresponding conditional Cramer-Rao bound (CCRB) and modified Cramer-Rao bound (MCRB) in multiple-input-multiple-output (MIMO) correlated flat-fading channels are derived. It is shown that the approximated ML algorithm in References [4,13] is just a special case of the DA ML estimator; while the extended squaring algorithm in Reference [14] is just a special case of the NDA ML estimator. For the DA case, the optimal orthogonal training sequences are also derived. It is found that the optimal orthogonal sequences resemble the Walsh sequences, but present different envelopes. Simulation results under different operating conditions (e.g. number of antennas and correlation between antennas) are given to assess and compare the performances of the DA and NDA ML estimators with respect to their corresponding CCRBs and MCRBs. It is found that (i) the mean square error (MSB) of the DA ML estimator is close to the CCRB and MCRB, (ii) the MSB of the NDA ML estimator is close to the CCRB but not to the MCRB, (iii) the MSEs of both DA and NDA ML estimators are approximately independent of the number of transmit antennas and are inversely proportional to the number of receive antennas, (iv) correlation between antennas has little effect on the MSEs of DA and NDA ML estimators and (v) DA ML estimator performs better than NDA ML estimator at the cost of lower transmission efficiency and higher implementation complexity. Copyright © 2004 John Wiley & Sons, Ltd.en_US
dc.languageengen_US
dc.publisherJohn Wiley & Sons Ltd. The Journal's web site is located at http://www3.interscience.wiley.com/cgi-bin/jhome/76507157en_US
dc.relation.ispartofWireless Communications and Mobile Computingen_US
dc.subjectCramer-Rao Bounden_US
dc.subjectData-Aideden_US
dc.subjectMaximum Likelihooden_US
dc.subjectMimo, Correlated Fadingen_US
dc.subjectNon-Data Aideden_US
dc.subjectOptimal Training Sequencesen_US
dc.subjectSymbol Timing Estimationen_US
dc.titleSymbol timing estimation in MIMO correlated flat-fading channelsen_US
dc.typeArticleen_US
dc.identifier.emailWu, YC:ycwu@eee.hku.hken_US
dc.identifier.authorityWu, YC=rp00195en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1002/wcm.251en_US
dc.identifier.scopuseid_2-s2.0-13244262786en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-13244262786&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume4en_US
dc.identifier.issue7en_US
dc.identifier.spage773en_US
dc.identifier.epage790en_US
dc.identifier.isiWOS:000225457000007-
dc.publisher.placeUnited Kingdomen_US
dc.identifier.scopusauthoridWu, YC=7406894786en_US
dc.identifier.scopusauthoridSerpedin, E=7003366947en_US

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