# Statistical Parameters of the First Order for Rayleigh Fading with Egc Diversity Kombiner

Topics: Cumulative distribution function, Diversity scheme, Fading Pages: 9 (2472 words) Published: August 25, 2013
Statistical parameters of the first order for Rayleigh Fading with EGC Diversity kombiner 1Borivoje Milosevic is with the Technical College University of Nis, A. Medvedeva 20, Nis 18000, Serbia, E-mail: borivojemilosevic@yahoo.com. 2Mihajlo Stefanovic is with the Faculty of Electronic Engineering, University of Niš, A. Medvedeva 14, Nis 18000, Serbia, 3Slobodan Obradovic is with the SANU, Beograd, Serbia

4Srdjan Jovkovic is with the Technical College University of Nis, A. Medvedeva 20, Nis 18000, Serbia

Borivoje Milosevic1 and Mihajlo Stefanovic 2

Abstract – This paper discusses the application of MATLAB tools for the realization of Rayleigh Fading using EGC diversity kombiner. In this paper the dual EGC ( Equal Gain Combiner ) Diversity system is consider. The ucorrelated Rayleigh fading is presented. The cumulative density function - CDF of the dual EGC output signals and the joint of output signal and its the first time derivative is determined. The probability density function -PDF of the dual EGC output signals and the joint of output signal and its the first time derivative is determined.

Keywords – EGC, PDF, CDF, Fading, Rayleigh, Combiner.

I. Introduction

PROBLEMS THAT OCCUR DURING THE IMPLEMENTATION OF APPLICATIONS FOR STATISTICAL ANALYSIS OF SIGNAL IN THE PRESENCE OF FADING MAINLY RELATED TO DIFFICULTIES IN EDITING FORMULAS AND EXPRESSIONS, THEIR COMPUTATION (MATHEMATICA), DRAWING GRAPHICS (ORIGIN), ETC. THIS PAPER PROVIDES A SIMPLER APPROACH TO SOLVING THIS PROBLEM, OF COURSE, USING ONE EXCELLENT TOOLS: MATLAB. Some of the most well-known diversity techniques are MRC ( Maximum Ratio Combining ), EGC (Eqal Gain Combining ) and SC ( Selection Combining ) [1]. Around them, EGC presents significant practical interest, because it provides performance comparable to MRC but with simpler implementation complexity. In EGC, the desired signals of the output of the two antenas is caphased, equally weighted and then summed to give the resultant desired signal. Diversity combining is one of the most practical, effective and widely emplayed techniqes in digital communication receivers for mitigating the effect of multipath fading and improving the overall wirless systems performance. The performance of EGC, assuming independet channel fading, has been studied extensively in the literature, although the published results concerning EGC receiver are less, compared with those of other the diversity methods, such are MRC and SC. Thos lack is mainly due to the difficulty of finding the probability density function ( PDF ) and cumulative distributions function ( CDF ) of the EGC output signal to noise ratio (SNV) (3(. However, independent fading is not always realised in practice due to insufficient antena spacing. Therevere, it is important to understand hav the correlation betwen received signals effect the offered diversity gain. From reintering the literature, there are few approaches for the performance evaluation of predetection EGC over correlated fading channels.

II. Exposition

A. CHOICE OF MATHEMATICAL METHODS AND MATHEMATICAL MODELING PROBLEMS

When analyzing the process of propagation of digital communication systems to be utilized methods and models of statistical theory of telecommunications. The accuracy of proposed model will be checked by deductive methods and simulation systems for known cases. In doing so, it is very important to set the criteria for selection of models, each of which has its advantages and disadvantages, which must be viewed through the purpose of a certain type of software.

When choosing to be analyzed:

• Why is purchased
• Who will use it
• What is the expected benefit

Analysis of previous factors significantly narrows the circle of appropriate tools. Within such a selection, the remaining tools we need to pay attention to the following factors:

• Flexibility of use
•...

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11] Mihajlo C