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Robust Adaptive Multiuser Detection for CDMA Frequency-Selective Fading Channels

Zhou, H, Xiao, P and Cowan, C (2010) Robust Adaptive Multiuser Detection for CDMA Frequency-Selective Fading Channels In: IEEE Vehicular Technology Conference, 2010-09-06 - 2010-09-09, Ottawa.

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Abstract

Robust adaptive multiuser detection schemes are developed for direct-sequence code-division multiple-access (DS-CDMA) multipath frequency-selective fading channels. Multiple access interference (MAI) and intersymbol interference (ISI) are presented in identical format in the expanded signal subspace, which provides convenience for symbol-by-symbol multiuser detection. The proposed multiuse detectors are designed in the expanded signal subspace, and subspace estimation and Kalman filtering algorithms are developed for their adaptive implementation. It is demonstrated by simulation that these adaptive detectors are robust against subspace estimation error and can effectively suppress both MAI and ISI and converge to the optimum SINR.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing
Authors :
AuthorsEmailORCID
Zhou, HUNSPECIFIEDUNSPECIFIED
Xiao, PUNSPECIFIEDUNSPECIFIED
Cowan, CUNSPECIFIEDUNSPECIFIED
Date : 4 October 2010
Identification Number : 10.1109/VETECF.2010.5594399
Contributors :
ContributionNameEmailORCID
PublisherIEEE, UNSPECIFIEDUNSPECIFIED
Additional Information : © YEAR 2010. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Depositing User : Symplectic Elements
Date Deposited : 20 Sep 2013 12:47
Last Modified : 23 Sep 2013 20:18
URI: http://epubs.surrey.ac.uk/id/eprint/799017

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