Multi-branch switched diversity with adaptive switching thresholds

Haewoon Nam*, Mohamed Slim Alouini

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

This paper investigates a simple analytical approach that yields the optimal switching thresholds for multibranch switched diversity systems. It also presents a performance optimization based on these optimal thresholds. For multi-branch switched diversity systems, the optimal fixed switching threshold is not only a function of the average channel SNR but also a function of the number of diversity branches. Conventional multi-branch switched diversity systems use a single fixed switching threshold, where computing this optimal threshold is not a simple task when the number of diversity branches is high. We propose a novel multibranch switched diversity system that is based on a set of adaptive switching thresholds instead of a single fixed switching threshold, where a different switching threshold is used every switching. Thanks to the fact that each switching threshold in the set depends only on the remaining diversity branches, the proposed system allows a simple optimization for these switching thresholds. Furthermore, numerical and simulation results show that the proposed adaptive switched diversity system outperforms the conventional system.

Original languageEnglish (US)
Title of host publication2008 International Symposium on Information Theory and its Applications, ISITA2008
DOIs
StatePublished - 2008
Externally publishedYes
Event2008 International Symposium on Information Theory and its Applications, ISITA2008 - Auckland, New Zealand
Duration: Dec 7 2008Dec 10 2008

Publication series

Name2008 International Symposium on Information Theory and its Applications, ISITA2008

Other

Other2008 International Symposium on Information Theory and its Applications, ISITA2008
Country/TerritoryNew Zealand
CityAuckland
Period12/7/0812/10/08

ASJC Scopus subject areas

  • General Computer Science

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