DocumentCode
3579563
Title
A unified approach for representing wireless channels using EM-based finite mixture of gamma distributions
Author
Alhussein, Omar ; Muhaidat, Sami ; Jie Liang ; Yoo, Paul D.
Author_Institution
Sch. of Eng. Sci., Simon Fraser Univ., Burnaby, BC, Canada
fYear
2014
Firstpage
1008
Lastpage
1013
Abstract
We present a unified framework to evaluate the error rate performance of wireless networks over generalized fading channels. In particular, we propose a new approach to represent different fading distributions by mixture of Gamma distributions. The new approach relies on the expectation-maximization (EM) algorithm in conjunction with the so-called Newton-Raphson maximization algorithm. We show that our model provides similar performance to other existing state-of-art models in both accuracy and simplicity, where accuracy is analyzed by means of mean square error (MSE). In addition, we demonstrate that this algorithm may potentially approximate any fading channel, and thus we utilize it to model both composite and non-composite fading models. We derive novel closed form expression of the raw moments of a dual-hop fixed-gain cooperative network. We also study the effective capacity of the end-to-end SNR in such networks. Numerical simulation results are provided to corroborate the analytical findings.
Keywords
Newton-Raphson method; cooperative communication; expectation-maximisation algorithm; fading channels; gamma distribution; mean square error methods; numerical analysis; EM-based finite mixture; Newton-Raphson maximization; dual-hop fixed-gain cooperative network; error rate performance; expectation-maximization; fading distributions; gamma distribution mixture; generalized fading channels; mean square error; numerical simulation; unified approach; wireless channels; wireless networks; Approximation algorithms; Approximation methods; Fading; Mathematical model; Relays; Signal to noise ratio; Wireless communication; Amplify-and-Forward (AF); Mixture of gamma distributions; dual-hop; expectation-maximization algorithms; semi-blind relaying;
fLanguage
English
Publisher
ieee
Conference_Titel
Globecom Workshops (GC Wkshps), 2014
Type
conf
DOI
10.1109/GLOCOMW.2014.7063565
Filename
7063565
Link To Document