Fading and Shadowing in Wireless Systems.
The author explores the impediments to efficient wireless transmission and techniques and proposes ways to mitigate these problems. Problems presented include both fading and shadowing, which increase the possibility of outrage in wireless systems.
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| Main Author | |
|---|---|
| Format | Electronic eBook |
| Language | English |
| Published |
Cham :
Springer International Publishing,
2017.
|
| Edition | 2nd ed. |
| Subjects | |
| Online Access | Full text |
| ISBN | 9783319531984 9783319531977 |
| Physical Description | 1 online resource (827 pages) |
Cover
Table of Contents:
- Preface to the Second Edition; Preface to the First Edition; Contents; Chapter 1: Overview; 1.1 Outline; References; Further Readings; Information on Software; Chapter 2: Concepts of Probability and Statistics; 2.1 Introduction; 2.2 Random Variables, Probability Density Functions, and Cumulative Distribution Functions; 2.3 Characteristic Functions, Moment Generating Functions and Laplace Transforms; 2.4 Some Commonly Used Probability Density Functions; 2.4.1 Beta Distribution; 2.4.2 Binomial Distribution; 2.4.3 Cauchy Distribution; 2.4.4 Chi-Squared Distribution; 2.4.5 Erlang Distribution.
- 2.4.6 Exponential Distribution2.4.7 F (Fisher-Snedecor) Distribution; 2.4.8 Gamma Distribution; 2.4.9 Generalized Gamma Distribution; 2.4.10 Inverse Gaussian (Wald) Distribution; 2.4.11 Laplace Distribution; 2.4.12 Lognormal Distribution; 2.4.13 Nakagami Distribution; 2.4.14 Non-Central Chi-Squared Distribution; 2.4.15 Normal (Gaussian) Distribution; 2.4.16 Poisson Distribution; 2.4.17 Rayleigh Distribution; 2.4.18 Rectangular or Uniform Distribution; 2.4.19 StudentÂś t Distribution; 2.4.20 Weibull Distribution; 2.5 Joint, Marginal and Conditional Densities.
- 2.6 Expectation, Covariance, Correlation, Independence, and Orthogonality2.7 Central Limit Theorem; 2.8 Transformation of Random Variables; 2.8.1 Derivation of the pdf and CDF of Y=g(X); 2.8.2 Probability Density Function of Z=X+Y; 2.8.3 Joint pdf of Functions of Two or More Random Variables; 2.8.4 Use of CHF to Obtain pdf of Sum of Random Variables; 2.8.5 Some Transformations of Interest in Wireless Communications; 2.9 Some Bivariate Correlated Distributions of Interest in Wireless Communications; 2.9.1 Bivariate Normal pdf; 2.9.2 Bivariate Nakagami pdf; 2.9.3 Bivariate Gamma pdf.
- 2.9.4 Bivariate Generalized Gamma pdf2.9.5 Bivariate Weibull pdf; 2.9.6 Bivariate Rician Distribution; 2.10 Order Statistics; 2.10.1 A Few Special Cases of Order Statistics in Wireless Communications; 2.11 Decision Theory and Error Rates; 2.11.1 Gaussian Case; 2.11.2 Non-Gaussian Case; 2.12 Upper Bounds on the Tail Probability; 2.12.1 Chebyshev Inequality; 2.12.2 Chernoff Bound; 2.13 Stochastic Processes; 2.14 Parameter Estimation and Testing; 2.14.1 Method of Moments; 2.14.2 Maximum Likelihood Estimation; 2.14.3 Comparison of MoM and MLE; 2.14.3.1 Gamma Distribution.
- 2.14.3.2 Generalized Gamma Density2.14.3.3 Generalized K Distribution; 2.14.3.4 Gamma-Lognormal (Shadowed Fading Channel); 2.15 Chi-Square Tests; 2.15.1 Exponential Density; 2.15.2 K Distribution; 2.16 MSE and Chi-Square Test; 2.17 Mixture Densities in Wireless Channel Modeling; 2.18 Receiver Operating Characteristics; 2.19 Laplace and Mellin Transforms; 2.19.1 Laplace Transforms and Sums of Random Variables; 2.19.1.1 Two Exponential Variables; 2.19.1.2 Two Identical Gamma Variable: G(m, a) and G(m, a); 2.19.1.3 Two Non-Identical Gamma Variables (Different Orders): G(m, a) and G(n, a).