Qureshi, Athar, Kanakis, Triantafyllos and Rapajic, Predrag (2010) Adaptive combining of signals with unequal noise variances. In: 2nd International Conference on Computational Intelligence, Modelling and Simulation (CIMSiM). IEEE Computer Society, Conference Publishing Services, Washington, USA, pp. 488-493. ISBN 978-1-4244-8652-6 (Print), 978-0-7695-4262-1 (Online) (doi:https://doi.org/10.1109/CIMSiM.2010.21)

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Abstract

This paper demonstrates the signal combining by use of adaptive algorithms for wireless communication networks. The adaptive combiner operates under different noise variances on each branch of the multi-antenna receiver. We utilise adaptive signal combining technique with least mean squares (LMS) algorithm based on Newton's Recursion Method. It is shown that the adaptive combining filter with LMS converges with respect to signal to noise ratio (SNR) and not to the transmit power Simulation results show that the Adaptive Combining technique proposed in this paper provides significant mean square error (MSE) improvement which reflects to BER performance improvement. This improvement is more obvious when two independent signals arrive at the receiver communication terminal (at different antennas) with 10dB of SNR difference, which is a very common situation in wireless communication systems.

Item Type:	Conference Proceedings
Title of Proceedings:	2nd International Conference on Computational Intelligence, Modelling and Simulation (CIMSiM)
Additional Information:	[1] First available online: 28 January 2011. [2] This paper was presented at the 2nd International Conference on Computational Intelligence, Modelling and Simulation (CIMSiM 2010) held from 28-30 September 2010 in Bali, Indonesia. [3] INSPEC Accession Number: 11793111.
Uncontrolled Keywords:	adaptive algorithms, wireless communication networks, noise variances, multi-antenna receiver adaptive signal combining, least mean squares (LMS) algorithm, Newton's recursion method, adaptive combining technique
Subjects:	Q Science > Q Science (General) Q Science > QA Mathematics Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Pre-2014 Departments:	School of Engineering School of Engineering > Department of Computer & Communications Engineering
Related URLs:	Publisher Publisher Organisation
Last Modified:	14 Oct 2016 09:19
URI:	http://gala.gre.ac.uk/id/eprint/7622

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