2026-09-18T20:48:53Zhttps://dspace.mit.edu/server/oai/request

oai:dspace.mit.edu:1721.1/166982022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023

Moe Z. Win. Gifford, Wesley M. (Wesley Michael), 1979- Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science 2005-05-17T14:58:26Z 2005-05-17T14:58:26Z 2004 2004 http://hdl.handle.net/1721.1/16698 57403228 Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004. Includes bibliographical references (p. 79-83). This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. This thesis presents a framework for evaluating the bit error probability of Nd-branch diversity combining in the presence of non-ideal channel estimates. The estimator structure is based on the maximum likelihood (ML) estimate and arises naturally as the sample mean of Np pilot symbols. The framework presented requires only the evaluation of a single integral involving the moment generating function of the norm square of the channel gain vector, and is applicable to channels with arbitrary distribution, including correlated fading. Analytical results show that the practical ML channel estimator preserves the diversity order of an Nd-branch diversity system, contrary to conclusions in the literature based upon a model that assumes a fixed correlation between the channel and its estimate. Finally, the asymptotic signal-to-noise ratio (SNR) penalty due to estimation error is investigated. This investigation reveals that the penalty has surprisingly little dependence on the number of diversity branches. by Wesley M. Gifford. S.M. 83 p. 475491 bytes 474953 bytes application/pdf application/pdf eng Massachusetts Institute of Technology M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 Electrical Engineering and Computer Science. Diversity with practical channel estimation in arbitrary fading environments Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="fa124dca-f47f-4f20-9ed5-d20d35fd6c17"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Diversity with practical channel estimation in arbitrary fading environments</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2004</PublicationDate> <Authors> <Author> <DisplayName>Gifford, Wesley M. (Wesley Michael), 1979-</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Electrical Engineering and Computer Science.</Keyword> <Abstract>This thesis presents a framework for evaluating the bit error probability of Nd-branch diversity combining in the presence of non-ideal channel estimates. The estimator structure is based on the maximum likelihood (ML) estimate and arises naturally as the sample mean of Np pilot symbols. The framework presented requires only the evaluation of a single integral involving the moment generating function of the norm square of the channel gain vector, and is applicable to channels with arbitrary distribution, including correlated fading. Analytical results show that the practical ML channel estimator preserves the diversity order of an Nd-branch diversity system, contrary to conclusions in the literature based upon a model that assumes a fixed correlation between the channel and its estimate. Finally, the asymptotic signal-to-noise ratio (SNR) penalty due to estimation error is investigated. This investigation reveals that the penalty has surprisingly little dependence on the number of diversity branches.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>