TY - JOUR

T1 - The κ-μ / Inverse Gamma and η-μ / Inverse Gamma Composite Fading Models

T2 - Fundamental Statistics and Empirical Validation

AU - Yoo, Seong Ki

AU - Simmons, Nidhi

AU - Cotton, Simon L.

AU - Sofotasios, Paschalis C.

AU - Matthaiou, Michail

AU - Valkama, Mikko

AU - Karagiannidis, George K.

N1 - Funding Information:
Manuscript received May 5, 2017; revised October 1, 2017; accepted November 16, 2017. Date of publication December 6, 2017; date of current version August 16, 2021. This work was supported in part by the U.K. Engineering and Physical Sciences Research Council under Grant No. EP/L026074/1, by the Department for the Economy Northern Ireland through Grant No. USI080 and by Khalifa University under Grant No. KU/FSU-8474000122 and Grant No. KU/RC1-C2PS-T2/8474000137. This paper was presented in part in IEEE PIMRC ’15, Hong Kong, China The associate editor coordinating the review of this paper and approving it for publication was O. Oyman. (Corresponding author: Paschalis C. Sofotasios.) S. K. Yoo was with the Institute of Electronics, Communications and Information Technology (ECIT), Queen’s University Belfast, Belfast BT3 9DT, U.K. He is now with the Centre for Data Science, Faculty of Engineering, Environment and Computing, Coventry University, Coventry CV1 2TL, U.K. (e-mail: [email protected]).
Publisher Copyright:
© 1972-2012 IEEE.

PY - 2021/8

Y1 - 2021/8

N2 - The \kappa -\mu / inverse gamma and \eta -\mu / inverse gamma composite fading models are presented and extensively investigated in this paper. We derive closed-form expressions for the fundamental statistics of the \kappa -\mu / inverse gamma composite fading model, such as the probability density function (PDF), cumulative distribution function (CDF). Additionally, we solve the associated integral that is commonly used to obtain the moment generating function (MGF) of statistical distributions to provide an MGF-Type function which is valid for performance analysis over the specified parameter space. Analytic expressions for the PDF, higher order moments and AF are also derived for the \eta -\mu / inverse gamma composite fading model, while infinite series expressions are obtained for the corresponding CDF and MGF-Type function. The suitability of the new models for characterizing composite fading channels is demonstrated through a series of extensive field measurements for wearable, cellular, and vehicular communications. For all of the measurements, two propagation geometry problems with special relevance to the two new composite fading models, namely the line-of-sight (LOS) and non-LOS (NLOS) channel conditions, are considered. It is found that both the \kappa -\mu / inverse gamma and \eta -\mu / inverse gamma composite fading models provide an excellent fit to fading conditions encountered in the field. The goodness-of-fit of these two composite fading models is also evaluated and compared using the resistor-Average distance. As a result, it is shown that the \kappa -\mu / inverse gamma composite fading model provides a better fit compared to the \eta -\mu / inverse gamma composite fading model when strong dominant signal components exist. On the contrary, the \eta -\mu / inverse gamma composite fading model outperforms the \kappa -\mu / inverse gamma composite fading model when there is no strong dominant signal component and/or the parameter \eta is not equal to unity, indicating that the scattered wave power of the in-phase and quadrature components of each cluster of multipath are not identical.

AB - The \kappa -\mu / inverse gamma and \eta -\mu / inverse gamma composite fading models are presented and extensively investigated in this paper. We derive closed-form expressions for the fundamental statistics of the \kappa -\mu / inverse gamma composite fading model, such as the probability density function (PDF), cumulative distribution function (CDF). Additionally, we solve the associated integral that is commonly used to obtain the moment generating function (MGF) of statistical distributions to provide an MGF-Type function which is valid for performance analysis over the specified parameter space. Analytic expressions for the PDF, higher order moments and AF are also derived for the \eta -\mu / inverse gamma composite fading model, while infinite series expressions are obtained for the corresponding CDF and MGF-Type function. The suitability of the new models for characterizing composite fading channels is demonstrated through a series of extensive field measurements for wearable, cellular, and vehicular communications. For all of the measurements, two propagation geometry problems with special relevance to the two new composite fading models, namely the line-of-sight (LOS) and non-LOS (NLOS) channel conditions, are considered. It is found that both the \kappa -\mu / inverse gamma and \eta -\mu / inverse gamma composite fading models provide an excellent fit to fading conditions encountered in the field. The goodness-of-fit of these two composite fading models is also evaluated and compared using the resistor-Average distance. As a result, it is shown that the \kappa -\mu / inverse gamma composite fading model provides a better fit compared to the \eta -\mu / inverse gamma composite fading model when strong dominant signal components exist. On the contrary, the \eta -\mu / inverse gamma composite fading model outperforms the \kappa -\mu / inverse gamma composite fading model when there is no strong dominant signal component and/or the parameter \eta is not equal to unity, indicating that the scattered wave power of the in-phase and quadrature components of each cluster of multipath are not identical.

KW - -μ fading model

KW - -μ fading model

KW - Channel modeling

KW - composite fading channel

KW - inverse gamma distribution

KW - resistor-Average distance.

UR - http://www.scopus.com/inward/record.url?scp=85037579777&partnerID=8YFLogxK

U2 - 10.1109/TCOMM.2017.2780110

DO - 10.1109/TCOMM.2017.2780110

M3 - Article

AN - SCOPUS:85037579777

SN - 0090-6778

VL - 69

SP - 5514

EP - 5530

JO - IEEE Transactions on Communications

JF - IEEE Transactions on Communications

IS - 8

M1 - 8166770

ER -