Abstract
In many communication systems training sequences are used to help the receiver identify and/or equalize the channel. The amount of training data required depends on the convergence properties of the adaptive filtering algorithms used for equalization. In this paper we propose the use of a new adaptive filtering method, interior point least squares (IPLS), for adaptive equalization. One of the main features of the algorithm is its fast transient convergence: it thus requires fewer training bits than for example RLS. We apply the IPLS algorithm to update the weight vector for a minimum-mean-square-error decision-feedback equalizer (MMSE-DFE)in a CDMA downlink scenario. Numerical simulations show that when training sequences are short IPLS consistently outperforms RLS in terms of system bit-error-rate. As the training sequence gets longer IPLS matches the performance of the RLS algorithm.
Original language | English (US) |
---|---|
Title of host publication | Signal Processing Theory and Methods I |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 5-8 |
Number of pages | 4 |
ISBN (Electronic) | 0780362934 |
DOIs | |
State | Published - 2000 |
Event | 25th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2000 - Istanbul, Turkey Duration: Jun 5 2000 → Jun 9 2000 |
Publication series
Name | ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings |
---|---|
Volume | 1 |
ISSN (Print) | 1520-6149 |
Other
Other | 25th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2000 |
---|---|
Country/Territory | Turkey |
City | Istanbul |
Period | 6/5/00 → 6/9/00 |
Bibliographical note
Publisher Copyright:© 2000 IEEE.