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.
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:|| 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.  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|
|School / Department / Research Groups:||School of Engineering
Faculty of Engineering & Science > School of Engineering
|Last Modified:||23 Oct 2012 13:21|
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