A generalized mixture of gaussians for fading channels

Omar Alhussein, Bassant Selim, Tasneem Assaf, Sami Muhaidat, Jie Liang, George K. Karagiannidis

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations

Abstract

The analysis of composite fading channels, which are typically encountered in wireless channels due to multipath and shadowing is quite involved, as the underlying fading distributions do not lend themselves to analysis. An example of such channels are the Nakagami/Rayleigh-Lognormal fading channels. Several simplified expressions have been proposed in the literature. In this paper, a generalized fading model for composite and non-composite fading models, based on the so-called Mixture of Gaussians (MoG) distribution, is proposed. The well-known expectation-maximization algorithm is utilized to estimate the parameters of the MoG model. Furthermore, relying on the proposed MoG model, we derive closed form expressions for several performance metrics used in wireless communication systems, including the raw moments, the amount of fading, the outage probability, the average channel capacity, and the moment generating function. In addition, the symbol error rate of L-branch maximum ratio combining diversity receiver is studied for linear coherent signaling schemes. Monte Carlo simulations are presented to corroborate the analytical results and to assess the accuracy of the MoG model.

Original languageBritish English
Title of host publication2015 IEEE 81st Vehicular Technology Conference, VTC Spring 2015 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479980888
DOIs
StatePublished - 1 Jul 2015
Event81st IEEE Vehicular Technology Conference, VTC Spring 2015 - Glasgow, United Kingdom
Duration: 11 May 201514 May 2015

Publication series

NameIEEE Vehicular Technology Conference
Volume2015
ISSN (Print)1550-2252

Conference

Conference81st IEEE Vehicular Technology Conference, VTC Spring 2015
Country/TerritoryUnited Kingdom
CityGlasgow
Period11/05/1514/05/15

Keywords

  • Composite distributions
  • Expectation-maximization algorithms
  • Fading channels
  • Gaussian mixture models
  • Maximum ratio combining
  • Performance analysis

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