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Simulations on the statistical properties for cascaded Rayleigh fading channel

Authors: Yazan Ibdah; Yanwu Ding; Hyuck M. Kwon; Kanghee Lee 0001;

Simulations on the statistical properties for cascaded Rayleigh fading channel

Abstract

In the past few years, mobile to mobile communication has gained much attention. Researchers have invested considerable effort in obtaining appropriate channel models to understand the statistical properties of the underlying channels. Generally, models can be classified into two groups, statistical and deterministic. In statistical models, a number of trials are required to obtain the desired properties by averaging simulation results. In deterministic models, a single trial is used to obtain desired properties. Deterministic models require much higher complexity compared to statistical models. In this paper, we study a statistical model based on a two-cascaded Raleigh principle. The proposed model requires fewer trials, has faster convergence rate, and it is less complex than some existing models. Monte Carlo simulations are provided for the first-order and second-order statistics of the proposed models for comparison with some existing models.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Average
Top 10%
Top 10%
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