The K - μ / inverse gamma fading model
Paper in proceeding, 2015

© 2015 IEEE. Statistical distributions have been extensively used in modeling fading effects in conventional and modern wireless communications. In the present work, we propose a novel κ - μ composite shadowed fading model, which is based on the valid assumption that the mean signal power follows the inverse gamma distribution instead of the lognormal or commonly used gamma distributions. This distribution has a simple relationship with the gamma distribution, but most importantly, its semi heavy-tailed characteristics constitute it suitable for applications relating to modeling of shadowed fading. Furthermore, the derived probability density function of the κ - μ / inverse gamma composite distribution admits a rather simple algebraic representation that renders it convenient to handle both analytically and numerically. The validity and utility of this fading model are demonstrated by means of modeling the fading effects encountered in body centric communications channels, which have been known to be susceptible to the shadowing effect. To this end, extensive comparisons are provided between theoretical and respective real-time measurement results. It is shown that these comparisons exhibit accurate fitting of the new model for various measurement set ups that correspond to realistic communication scenarios.

Author

S.K. Yoo

Queen's University Belfast

S.L. Cotton

Queen's University Belfast

P. Sofotasios

Tampere University of Technology

Aristotle University of Thessaloniki

Michail Matthaiou

Chalmers, Signals and Systems, Signal Processing and Biomedical Engineering

M. Valkama

Tampere University of Technology

G. K. Karagiannidis

Khalifa University

Aristotle University of Thessaloniki

IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC

Vol. 2015-December 425-429
978-146736782-0 (ISBN)

Subject Categories

Telecommunications

DOI

10.1109/PIMRC.2015.7343336

ISBN

978-146736782-0

More information

Latest update

5/14/2018