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Abstract:Wireless sensor networks deployed within metallic cavities are known to suffer from a very severe fading, even in strong line-of-sight propagation conditions. This behavior is well-captured by the Two-Wave with Diffuse Power (TWDP) fading distribution, which shows great fit to field measurements in such scenarios. In this paper, we address the joint estimation of the parameters K and ∆ that characterize the TWDP fading model, based on the observation of the received signal envelope. We use a moment-based approach to derive closed-form expressions for the estimators of K and ∆, as well as closed-form expressions for their asymptotic variance. Results show that the estimation error is close to the Cramer-Rao lower bound for a wide range of values of the parameters K and ∆. The performance degradation due to a finite number of observations is also analyzed.

We here present a general and tractable fading model for line-of-sight (LOS) scenarios, which is based on the product of two independent and non-identically distributed κµ shadowed random variables. Simple closed-form expressions for the probability density function and cumulative distribution function are derived, which are as tractable as the corresponding expressions derived from a product of Nakagami-m random variables. This newly proposed model simplifies the challenging characterization of LOS product channels, as well as combinations of LOS channels with non-LOS ones. Results are used to analyze performance measures of interest in the context of wireless powered communications.

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Let W 1 and W 2 be independent n×n complex central Wishart matrices with m 1 and m 2 degrees of freedom respectively. This paper is concerned with the extreme eigenvalue distributions of double-Wishart matrices (W 1 + W 2 ) −1 W 1 , which are analogous to those of F matrices W 1 W −1 2 and those of the Jacobi unitary ensemble (JUE). Defining α 1 = m 1 − n and α 2 = m 2 − n, we derive new exact distribution formulas in terms of (α 1 + α 2 )-dimensional matrix determinants, with elements involving derivatives of Legendre polynomials.This provides a convenient exact representation, while facilitating a direct large-n analysis with α 1 and α 2 fixed (i.e., under the so-called "hard-edge" scaling limit); the analysis is based on new asymptotic properties of Legendre polynomials and their relation with Bessel functions that are here established. Specifically, we present limiting formulas for the smallest and largest eigenvalue distributions as n → ∞ in terms of α 1 -and α 2 -dimensional determinants respectively, which agrees with expectations from known universality results involving the JUE and the Laguerre unitary ensemble (LUE). We also derive finite-n corrections for the asymptotic extreme eigenvalue distributions under hard-edge scaling, giving new insights on universality by comparing with corresponding correction terms derived recently for the LUE. Our derivations are based on elementary algebraic manipulations, differing from existing results on double-Wishart and related models which often involve Fredholm determinants, Painlevé differential equations, or hypergeometric functions of matrix arguments.