Advances in Statistical Channel Modeling for Wireless Communications (original) (raw)

Statistical analysis and channel modeling in next generation wireless communication systems

2021

In this thesis, statistical analysis and channel modeling in next generation wireless communication systems is presented in detail. The primary focus of this thesis is on the statistical modeling of interference temperature (IT) in cognitive radio systems, and empirical study of wireless channel characterization of unmanned aerial vehicle (UAV)-assisted communications at ultra-wideband (UWB) and at millimeter wave (mmWave) frequencies.Firstly, in the cognitive radio system, a novel idea to statistically model the dynamic interference threshold (IT) from user traffic demand is presented in detail. It is shown that the cognitive radio system with dynamic IT will have high capacity performance with less outage probability over a system that does not utilize dynamic IT. The detailed theoretical analysis with expressions for mean capacity and outage probability in general operation region, and in high power region are derived and subsequently, validated with the simulations results. In a...

Review Paper on Second Order Statistics ofVarious Fading Channels

International Journal of Advanced Research in Electrical, Electronics and Instrumentation Energy, 2014

Radio-wave propagation through wireless channel is a complicated phenomenon characterized by fading which is the result of multipath propagation. In wireless communication system, random process associated with fading channels can usually characterized by their PDF (Probability Density Function) and CDF (Cumulative Distribution Function). Signal fading can drastically affect the performance of terrestrial communication systems. Several statistical models are available for describing the fading envelope of the received signal in which Rayleigh, Rician and Nakagami are the most frequently applied models. Higher-order statistics such as Level Crossing Rate (LCR) & Average Fade Duration render (AFD) insight into signals which is not always available at lower orders.

Paper on Second Order Statistics of Various Fading Channels

2014

Radio-wave propagation through wireless channel is a complicated phenomenon characterized by fading which is the result of multipath propagation. In wireless communication system, random process associated with fading channels can usually characterized by their PDF (Probability Density Function) and CDF (Cumulative Distribution Function). Signal fading can drastically affect the performance of terrestrial communication systems. Several statistical models are available for describing the fading envelope of the received signal in which Rayleigh, Rician and Nakagami are the most frequently applied models. Higher-order statistics such as Level Crossing Rate (LCR) & Average Fade Duration render (AFD) insight into signals which is not always available at lower orders.

Wireless Channel Models Ana Aguiar, James Gross

In this technical report analytical models of wireless channels are presented. The report addresses the reader interested in the various effects, which lead to the well known, unreliable and stochastic nature of wireless channels. The report is composed from various other books, reports and so, due to the reason that a comprehensive, but still easy understandable discussion of the matter for engineers working on protocols is hard to find. Instead many other presentations are quite specific, deal only with a certain amount of the ...

On the Estimation of the α-μ Channel Signal Fading Distribution Parameters

American Journal of Applied Mathematics and Statistics, 2020

Radio channel signals are heavily used tool in telecommunications. A suitable probability distribution is needed to model signals. Many probability distributions have been introduced for this purpose. The α-μ probability distribution is a general channel signal fading model that encompasses many applied important distributions as a special case. This distribution is also known as generalized gamma, Stacy distribution. This distribution is used to describe the fading mobile radio signal under a general diffuse scattering. The main advantage of this probability distribution is that it is flexible and mathematically tractable. Also, many other distributions can be considered as a special case of α-μ probability distribution. In this article we discuss the model parameters' estimation. Two new maximum likelihood (ML) and Psi-inverse (PI) estimators for the α-μ channel signal fading distribution have been proposed. Simulation study is finally conducted to evaluate the performance of ...

The N * Nakagami Fading Channel Model

2005 2nd International Symposium on Wireless Communication Systems, 2005

A generic distribution, referred to as N* Nakagami, constructed as the product of N statistically independent, but not necessarily identically distributed, Nakagami-m random variables (RV)s, is introduced and analyzed. The proposed distribution turns out to be an extremely convenient tool for analyzing the performance of digital communication systems over generalized fading channels. The main result contributions of the paper are two-fold. Firstly, the moments-generating function (MGF), probability density function, cumulative distribution function (CDF), and moments of the N* Nakagami distribution are derived in closed-fonn. Using these formulae, generic closedform expressions for the outage probability, amount of fading, and average symbol error probability for several binary and multilevel modulation signals of digital communication systems operating over the N* Nakagami fading channel model are presented. Various numerical and computer simulation results verify the correctness of the proposed formulation. Secondly, the suitability of the N* Nakagami fading distribution to approximate the Lognormal distribution is being investigated. Using Kolmogorov-Smirnov tests, the rate of convergence of the central limit theorem as pertaining to the multiplication of RVs is quantified.

Modeling and Analysis of Wireless Channels via the Mixture of Gaussian Distribution

IEEE Transactions on Vehicular Technology, 2015

Considerable efforts have been devoted to statistical modeling and the characterization of channels in a range of statistical models for fading channels. In this paper, we consider a unified approach to model wireless channels by the mixture of Gaussian (MoG) distribution. Simulations provided have shown the new probability density function to accurately characterize multipath fading as well as composite fading channels. We utilize the well known expectation-maximization algorithm to estimate the parameters of the MoG model and further utilize the Kullback-Leibler divergence and the mean square error criteria to demonstrate that our model provides both high accuracy and low computational complexity, in comparison with existing results. Additionally, we provide closed form expressions for several performance metrics used in wireless communication systems, including the moment generating function, the raw moments, the amount of fading, the outage probability, the average channel capacity, and the probability of energy detection for cognitive radio. Numerical Analysis and Monte-Carlo simulations are presented to corroborate the analytical results and to provide detailed performance comparisons with the other models in the literature.

New analytical models and probability density functions for fading in wireless communications

IEEE Transactions on Communications, 2002

This paper presents new envelope probability density functions (pdfs) that describe small-scale, local area fading experienced by narrow-band wireless receivers. The paper also develops novel pdfs that describe the local area fading of two specular multipath components in the presence of other diffusely propagating waves. These pdfs are studied in the context of classical fading pdfs such as the Rayleigh, Rician, and other distributions.