Adaptive channel estimation using least mean squares algorithm for cyclic prefix OFDM systems
conference contribution
posted on 2025-05-10, 22:57 authored by Ling E. Pooh, Wee Gin Lim, Ali HassanOrthogonal frequency division multiplexing (OFDM) delivers high data transmission rate and forms the basis of Beyond 3G. The channel estimation is imperative for the implementation of OFDM. Cyclic Prefix (CP) based block Recursive Least Squares (RLS) channel estimation algorithm has been proposed for OFDM systems but it increases computational complexity. In this paper, we propose a block LMS (Least Mean Squares) channel estimation algorithm which promises less computation but delivers comparable and promising results.
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Source title
Proceedings: 2009 IEEE 9th Malaysia International Conference on Communications with a Special Workshop on Digital TV Contents, MICC 2009Name of conference
IEEE 9th Malaysia International Conference on Communications (MICC 2009)Location
Kuala Lumpur, MalaysiaStart date
2009-12-15End date
2009-12-17Pagination
789-793Publisher
Institute of Electrical and Electronics Engineers (IEEE)Place published
Piscataway, NJLanguage
- en, English
College/Research Centre
Faculty of Engineering and Built EnvironmentSchool
School of Electrical Engineering and Computer ScienceRights statement
Copyright © 2009 IEEE. Reprinted from the Proceedings: 2009 IEEE 9th Malaysia International Conference on Communications with a Special Workshop on Digital TV Contents, MICC 2009. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of University of Newcastle's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.Usage metrics
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