Please use this identifier to cite or link to this item: https://doi.org/10.1049/ip-com:20010274
Title: Adaptive least mean square CDMA detection with gram-schmidt pre-processing
Authors: Gong, Y.
Lim, T.J.
Farhang-Boroujeny, B. 
Issue Date: Aug-2001
Source: Gong, Y., Lim, T.J., Farhang-Boroujeny, B. (2001-08). Adaptive least mean square CDMA detection with gram-schmidt pre-processing. IEE Proceedings: Communications 148 (4) : 249-254. ScholarBank@NUS Repository. https://doi.org/10.1049/ip-com:20010274
Abstract: 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.
Source Title: IEE Proceedings: Communications
URI: http://scholarbank.nus.edu.sg/handle/10635/69185
ISSN: 13502425
DOI: 10.1049/ip-com:20010274
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

3
checked on Dec 6, 2017

WEB OF SCIENCETM
Citations

2
checked on Nov 18, 2017

Page view(s)

17
checked on Dec 10, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.