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The Statistical Model Recognition of the Radio Channel and Its Application in MIMO Systems

Author: ZongHuLiang
Tutor: ZengMingRu
School: Nanchang University
Course: Control Theory and Control Engineering
Keywords: modeling of radio channel probability density function law recognition mixture model MIMO information criterion EM algorithm
CLC: TN919.3
Type: Master's thesis
Year: 2011
Downloads: 19
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Abstract


Modeling of radio channel behavior is very important for digital communication. It is the reason why several propagation models have been implemented to reducethe effect of fast fading to the radio channel which is caused by the phenomena of multipath. So, there exist some methods to find the one which best coincides with radio channel behavior among the different statistical laws. By opposition with the classical Kolmogorov-Smirnov method based on cumulative distribution function, we consider the others method based on histogram, mixture model and IC allowing compute Kullback-Leibler distances between theoretical probability densities and empirical probability densities. Those distances are then used for the recognition of the law.The objective of this article is to compare and analyze the performances of ours identification methods by statistical method. We analyze the three laws of Rayleigh, Weibull and Nakagami models usually considered in two situations:supervised and unsupervised. Then, we can find that the the method of Kullback-Leibler using the histogram more reliable than others. Moreover, we apply this method for law recognition in a real setup where data come from radio channel propagation experimentation.Finally, to follow the development of new technologies and meet the requirements of high transmission rates, we apply this method to MIMO system in two dimensions. The experiments show that Webuill fading model is more suitable for modeling of the wireless channel in the one-dimensional and two-dimensional environment we researched.

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