Abstract

In this paper, a novel form of the folded normal (FN) distribution has been proposed to model the small-scale fading in wireless communications. From a multiple-input multiple-output (MIMO) measurement campaign conducted in a lab environment with the line-of-sight (LOS) conditions at both the 60 and the 94 GHz bands, the authors obtain the parameters of the Rician, FN, and k-μ distributions. These parameters have been calculated by using the least square (LS) approximation and with techniques of statistical inference. The FN distribution provides the best fitting to the experimental results using the Kolmogorov-Smirnov (K-S) test for the inferred estimators with values of the fulfillment of 100% and 69.82% at the 60 and 94 GHz bands, respectively, for a significance level of 1%.

Highlights

  • The received envelope in a wireless communication channel experiments two physical effects

  • It is worth noting that 2 048 distributions and 1 024 distributions at the 60 and 94 GHz bands, respectively, have been approximated and estimated in each one of the positions corresponding to each frequency sample

  • The κf parameter of the folded normal (FN) distribution is expressed as a function of an equivalent Rician K -factor, which is widely used in the literature

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Summary

INTRODUCTION

The received envelope in a wireless communication channel experiments two physical effects. J. Reig et al.: Folded Normal Distribution: A New Model for the Small-Scale Fading in LOS Condition shadowed distribution includes the κ-μ and η-μ distributions as particular cases [13] in a mathematically tractable model. Reig et al.: Folded Normal Distribution: A New Model for the Small-Scale Fading in LOS Condition shadowed distribution includes the κ-μ and η-μ distributions as particular cases [13] in a mathematically tractable model Some of these distributions have been recently applied to model new propagation scenarios [14], [15]. The applicability of using the FN distribution to model the small-scale fading is mainly underlined for the high dependence of the performance parameters such as the average error probability and outage probability using different modulation schemes on the Rician K -factor [30].

FAMILY OF κ-μ DISTRIBUTIONS
RICIAN
RELATIONSHIP WITH OTHER DISTRIBUTIONS
MEASUREMENTS DESCRIPTION
PARAMETER INFERENCE USING ESTIMATORS
RESULTS
K-S TEST USING LS APPROXIMATION
CONCLUSIONS
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