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Multipath Propagation Fade Duration Modeling of Land Mobile Satellite Radio Channel

Date

Type

folyóiratcikk

Reading access rights:

Open access

ISSN, e-ISSN

0018-2028

Periodical Number

7

Periodical Volume

LXII

Container Title

Híradástechnika

Version

Postprint

First Page

22

Subject Area

Műszaki tudományok

Subject Field

Villamosmérnöki tudományok

Subject (OSZKAR)

multipath propagation
fade duration
partitioned Markov chain
Fritchman model

Gender

Tudományos cikk

OOC works

Abstract

The propagation on a Land Mobile Satellite (LMS) radio link is highly influenced by the shadowing effects of buildings and vegetation, or by the multipath propagation. This kind of fading arises due the multiple reflexions of the radio waves on the surrounding objects; therefore not only the direct signal is received. The characteristics of fading highly depend on the surroundings. During the design of LMS radio links one can apply the distribution function of the attenuation or the fade duration statistics to determine the fluctuation of the received signal. The fade duration is an important dynamic parameter of the path attenuation which gives the duration of fading higher than a given attenuation threshold. Therefore the fade duration is always calculated formultiple threshold levels. In our contribution a digital model with Markov chain will be introduced, which is also applicable to determine the statistical parameters of the fade duration. The model is based on the measurement data of a real LMS channel what has been used to calculate the model parameters. The proposed model is a partitioned Fritchman’s Markov chain which is applicable to describe the stochastic fade duration process and also to calculate the Complementary Cumulative Distribution Function (CCDF) of the fade duration. The expressions to calculate the model parameter dependency on the threshold level will be also introduced. Therefore the model will be applicable to calculate the CCDF of fade duration for any desired threshold level which may lead us in the future to the synthesis of attenuation time series.

Description

Keywords