Skip navigation

Adaptive AR channel model identification of time-varying communication systems

Adaptive AR channel model identification of time-varying communication systems

Krasevac, Zarko B. and Rapajic, Predrag B. (2008) Adaptive AR channel model identification of time-varying communication systems. In: 2008 IEEE 10th International symposium on spread spectrum techniques and applications. IEEE Conference Publications . Institute of Electrical and Electronics Engineers, Inc., Piscataway, NJ, USA, pp. 618-622. ISBN 9781424422036 (doi:10.1109/ISSSTA.2008.121)

Full text not available from this repository.

Abstract

This paper implements an adaptive identification of autoregressive AR model coefficients for model-based filtering over time-varying communication channels. The presented approach does not require a-priori knowledge of the dynamics of the system which overcomes the issue of determining model coefficients that capture the dynamics of unknown time-varying channels. Simulation MSE performance analysis in a multiuser environment shows superior experimental performance of the AR(2) model-based adaptive algorithm with adaptive model identification, comparing to the AR(1) model-based adaptive algorithm with adaptive model identification, the same algorithm with fixed model coefficients and standard observation-only based LMS and RLS adaptive algorithms.

Item Type: Conference Proceedings
Title of Proceedings: 2008 IEEE 10th International symposium on spread spectrum techniques and applications
Additional Information: [1] This paper was first presented at the 2008 IEEE 10th International Symposium on Spread Spectrum Techniques and Applications (ISSSTA2008), held from 25-28 August 2008 in Bologna, Italy. [2] First published online: 05 September 2008
Uncontrolled Keywords: adaptive algorithm, adaptive equalizers, adaptive filters, channel estimation, communication channels, equations, filtering, Kalman filters, time varying systems, time-varying channels
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Pre-2014 Departments: School of Engineering
Related URLs:
Last Modified: 14 Oct 2016 09:22
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/9106

Actions (login required)

View Item View Item