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Adaptive least mean square CDMA detection with Gram–Schmidt pre-processing

Gong, Y., Lim, T. J. and Farhang-Boroujeny, B. (2001) Adaptive least mean square CDMA detection with Gram–Schmidt pre-processing. IEE Proceedings: Communications, 148 (4). pp. 249-254. ISSN 1350-2425

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To link to this article DOI: 10.1049/ip-com:20010274

Abstract/Summary

The Gram-Schmidt (GS) orthogonalisation procedure has been used to improve the convergence speed of least mean square (LMS) adaptive code-division multiple-access (CDMA) detectors. However, this algorithm updates two sets of parameters, namely the GS transform coefficients and the tap weights, simultaneously. Because of the additional adaptation noise introduced by the former, it is impossible to achieve the same performance as the ideal orthogonalised LMS filter, unlike the result implied in an earlier paper. The authors provide a lower bound on the minimum achievable mean squared error (MSE) as a function of the forgetting factor λ used in finding the GS transform coefficients, and propose a variable-λ algorithm to balance the conflicting requirements of good tracking and low misadjustment.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Science > School of Systems Engineering
ID Code:19165
Uncontrolled Keywords:CDMA detectors, GS orthogonalisation procedure, GS transform coefficients, Gram-Schmidt pre-processing, LMS adaptive code-division multiple-access, adaptation noise, adaptive least mean square CDMA detection, convergence speed, forgetting factor, minimum achievable mean squared error, misadjustment, performance, tap weights, tracking, variable-λ algorithm
Publisher:IET

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