A Generalized Mixture of Gaussians Model for Fading Channels

被引:0
|
作者
Alhussein, Omar [1 ]
Selim, Bassant [2 ]
Assaf, Tasneem [2 ]
Muhaidat, Sami [1 ,2 ,3 ]
Liang, Jie [1 ]
Karagiannidis, George K. [2 ,4 ]
机构
[1] Simon Fraser Univ, Sch Engn Sci, Burnaby, BC V5A 1S6, Canada
[2] Khalifa Univ Sci Technol & Res, Abu Dhabi, U Arab Emirates
[3] Univ Surrey, CCSR, Guildford GU2 5XH, Surrey, England
[4] Aristotle Univ Thessaloniki, Thessaloniki 54124, Greece
关键词
Fading channels; composite distributions; expectation-maximization algorithms; Gaussian mixture models; maximum ratio combining; performance analysis; PERFORMANCE ANALYSIS;
D O I
暂无
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
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.
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页数:6
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