Abstract

In this paper, we perform a systematic investigation of the statistics associated with the product of two independent and non-identically distributed $\kappa$ – $\mu$ random variables. More specifically, we develop novel analytical formulations for many of the fundamental statistics of interest, namely, the probability density function, cumulative distribution function, and moment-generating function. Using these new results, closed-form expressions are obtained for the higher order moments, amount of fading and channel quality estimation index, while analytical formulations are obtained for the outage probability, average channel capacity, average symbol error probability, and average bit error probability. These general expressions can be reduced to a number of fading scenarios, such as the double Rayleigh, double Rice, double Nakagami- $m$ , $\kappa$ – $\mu$ /Nakagami- $m$ , and Rice/Nakagami- $m$ , which all occur as special cases. Additionally, as a byproduct of the work performed here, formulations for the $\kappa$ – $\mu /\kappa$ – $\mu$ composite fading model can also be deduced. To illustrate the efficacy of the novel expressions proposed here, we provide useful insights into the outage probability of a dual-hop system used in body area networks, and demonstrate the suitability of the $\kappa$ – $\mu /\kappa$ – $\mu$ composite fading for characterizing shadowed fading in device-to-device channels.

Highlights

  • T HE product of random variables (RVs) is of great importance as it finds application in a broad range of wireless communication systems

  • Closedform expressions are obtained for the higher order moments, amount of fading and channel quality estimation index, while analytical formulations are obtained for the outage probability, average channel capacity, average symbol error probability, and average bit error probability

  • Novel analytical expressions are derived for the probability density function (PDF), cumulative distribution function (CDF) and moment-generating function (MGF) of the product of two κ-μ RVs

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Summary

INTRODUCTION

T HE product of random variables (RVs) is of great importance as it finds application in a broad range of wireless communication systems. Small-scale fading results from multipath scattering, whereas shadowing is introduced by the topographical elements and objects obstructing the signal path To model these propagation mechanisms, several statistical distributions have been proposed. Κ represents the ratio of the total power of the dominant components to the total power of the scattered waves whilst μ represents the number of multipath clusters It is a very general model and contains other important distributions such as the Rice (κ = K , μ = 1), Nakagami-m (κ → 0, μ = m), Rayleigh (κ → 0, μ = 1) and One-Sided Gaussian (κ → 0, μ = 0.5) as special cases. It is worth remarking that these expressions are very flexible and encompass a number of other fading scenarios such as the double Rayleigh, double Rice, double Nakagami-m, double One-Sided Gaussian and product mixtures of these fading models as special cases.

DEFINITION
PDF and CDF of the Double κ-μ Fading Model
Moment Generating Function
Higher Order Moments
PERFORMANCE ANALYSIS AND APPROXIMATE EXPRESSIONS
Amount of Fading
Channel Quality Estimation Index
Average Symbol and Bit Error Probability
Approximate Closed-Form Expressions
Some Special Cases
Numerical Results
BAN Communications
D2D Communications
CONCLUSION
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