Performance analysis of selection diversity over exponentially correlated α– µ fading environment
✍ Scribed by Zoran Popović; Stefan R. Panić; Jelena Anastasov; Petar Spalević; Mihajlo Stefanović
- Publisher
- John Wiley and Sons
- Year
- 2011
- Tongue
- English
- Weight
- 391 KB
- Volume
- 24
- Category
- Article
- ISSN
- 1074-5351
- DOI
- 10.1002/dac.1200
No coin nor oath required. For personal study only.
✦ Synopsis
Abstract
An approach to the performance analysis of multibranch selection combiner (SC) receiver operating over fading channels is presented. High level of generality for the proposed analysis is achieved by considering correlated α– µ fading environment. The effect of correlation is studied by assuming exponential correlation model of the signals in each diversity branch. The whole analysis is observed in the interference‐limited fading environments (SIR‐based diversity system is assumed). The important performance measures are considered. Closed form of formulae for the output SIR's probability density function and cumulative distribution function are derived. In order to check the accuracy of the complete proposed formulation, some numerical results are presented. Copyright © 2011 John Wiley & Sons, Ltd.
📜 SIMILAR VOLUMES
In this paper, an approach to the performance analysis of dual-branch switch-and-stay combining (SSC) diversity receiver, operating over correlated a-l fading channels in the presence of co-channel interference (CCI), is presented. Very useful novel infinite series expressions are obtained for the p
This paper studies the performance of switch and stay combining (SSC) diversity in the presence of cochannel interference over correlated Weibull fading channels. SSC diversity based on signal-to-interference ratio (SIR) is a low-complexity and a very efficient technique that reduces fading and co-c
## Abstract In this paper, the performance of L‐branch selection combining receiver over correlated Weibull fading channels in the presence of correlated Weibull‐distributed cochannel interference is analyzed. Closed‐form expressions for probability density function and cumulative distribution func