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The κ-μ Shadowed Fading Model with Integer Fading Parameters

F. Javier Lopez-Martinez, Jose F. Paris, Juan M. Romero-Jerez

Abstract

We show that the popular and general κ-μ shad- owed fading model with integer fading parameters μ and m can be represented as a mixture of squared Nakagami (or Gamma) distributions. Thus, its PDF and CDF can be expressed in closed-form in terms of a finite number of elementary functions (powers and exponentials). The main implications arising from such connection are then discussed, which can be summarized as: (1) the performance evaluation of communication systems operating in κ-μ shadowed fading becomes as simple as if a Nakagami fading channel was assumed; (2) the κ-μ shadowed distribution can be used to approximate the κ-μ distribution us- ing a closed-form representation in terms of elementary functions, by choosing a sufficiently large value of m; and (3) restricting the parameters μ and m to take integer values has limited impact in practice when fitting the κ-μ shadowed fading model to field measurements. As an application example, the average channel capacity of communication systems operating under κ-μ shadowed fading is obtained in closed-form.

The κ-μ Shadowed Fading Model with Integer Fading Parameters

Abstract

We show that the popular and general κ-μ shad- owed fading model with integer fading parameters μ and m can be represented as a mixture of squared Nakagami (or Gamma) distributions. Thus, its PDF and CDF can be expressed in closed-form in terms of a finite number of elementary functions (powers and exponentials). The main implications arising from such connection are then discussed, which can be summarized as: (1) the performance evaluation of communication systems operating in κ-μ shadowed fading becomes as simple as if a Nakagami fading channel was assumed; (2) the κ-μ shadowed distribution can be used to approximate the κ-μ distribution us- ing a closed-form representation in terms of elementary functions, by choosing a sufficiently large value of m; and (3) restricting the parameters μ and m to take integer values has limited impact in practice when fitting the κ-μ shadowed fading model to field measurements. As an application example, the average channel capacity of communication systems operating under κ-μ shadowed fading is obtained in closed-form.

Paper Structure

This paper contains 12 sections, 5 theorems, 36 equations, 11 figures, 1 table.

Key Result

Theorem 1

Let $\gamma$ be a random variable such that $\gamma \sim \mathcal{S}\left( {\bar{\gamma} ;\kappa ,\mu ,m} \right)$ and let $\mu,m \in {\mathbb N}$. Then, $\gamma$ is a mixture of squared Nakagami distributions, which PDF is given as follows: $\bullet$ If $m<\mu$ $\bullet$ If $m \geq \mu$ where and where we have defined with

Figures (11)

  • Figure 1: Convergence in distribution between the $\kappa$-$\mu$ shadowed distribution and the $\kappa$-$\mu$ distribution as $m\rightarrow\infty$. Parameter values $\kappa=5$, $\mu=3$ and $\bar{\gamma}=1$.
  • Figure 2: Gamma approximation to the Rician distribution with parameter $K$ using the Rician shadowed distribution with parameter $K$ and integer $m$. Parameter values $K=3$ and $\bar{\gamma}=1$. Nakagami approximation Nakagami1960 uses $\hat{m} = (1+K)^2/(1+2K)=2.28$.
  • Figure 3: Gamma approximation to the Rician distribution with parameter $K$ using the Rician shadowed distribution with parameter $K$ and integer $m$. Parameter values $K=10$ and $\bar{\gamma}=1$. Nakagami approximation Nakagami1960 uses $\hat{m} = (1+K)^2/(1+2K)=5.76$.
  • Figure 4: Evolution of the $\kappa$-$\mu$ shadowed fading PDF for different values of $\mu$. Solid lines correspond to real-valued $\mu\in\{1.5,2.5,3.5,4.5\}$, whereas dashed lines correspond to the largest previous and the smallest following integer values $\mu\in\{1:5\}$. Parameter values $\kappa=6$, $m=2$ and $\bar{\gamma}=1$.
  • Figure 5: Evolution of the $\kappa$-$\mu$ shadowed fading PDF for different values of $m$. Solid lines correspond to real-valued $m\in\{1.5,2.5,3.5,4.5,5.5\}$, whereas dashed lines correspond to the largest previous and the smallest following integer values $m\in\{1:6\}$. Parameter values $\kappa=6$, $\mu=2$ and $\bar{\gamma}=1$.
  • ...and 6 more figures

Theorems & Definitions (13)

  • Definition 1
  • Definition 2
  • Definition 3
  • Theorem 1
  • proof
  • Corollary 1
  • proof
  • Lemma 1
  • proof
  • Lemma 2
  • ...and 3 more