Performance of RLMS algorithm in adaptive array beam forming

Srar, Jalal; Chung, Kah-Seng

doi:10.1109/ICCS.2008.4737233

119211_Performance%20of%20RLMS%20Algorithm.pdf (190.9Kb)

Access Status

Open access

Authors

Srar, Jalal

Chung, Kah-Seng

Date

2008

Type

Conference Paper

Metadata

Show full item record

Citation

Srar, Jalal and Chung, Kah-Seng. 2008. Performance of RLMS algorithm in adaptive array beam forming, in ICCS 2008 Technical Program Committee (ed), 11th IEEE Singapure International Conference on Communications Systems, Nov 19 2008, pp. 493-498. Guangzhou, China: Institute of Electrical and Electronics Engineers (IEEE).

Source Title

Proceedings of the 11th IEEE International Conference on Communications Systems ICCS 2008

Source Conference

11th IEEE Singapure International Conference on Communications Systems ICCS 2008

DOI

10.1109/ICCS.2008.4737233

ISBN

9781424424245

Faculty

School of Electrical Engineering and Computing

Department of Electrical and Computer Engineering

Faculty of Science and Engineering

Remarks

Copyright © 2008 IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.

URI

http://hdl.handle.net/20.500.11937/12403

Collection

Curtin Research Publications

Abstract

This paper examines the performance of an adaptive linear array employing the new RLMS algorithm, which consists of a recursive least square (RLS) section followed by a least mean square (LMS) section. The performance measures used are output and input signal-to-interference plus noise ratios (SINR), side lobe level (SLL), and SINRo as a function of the direction of arrival of the interfering signal. Computer simulation results show that the performance of RLMS is superior to either the RLS or LMS based on these measures, particularly when operating with low input SINR.