A Simplified Posteriori Estimator to Cascade Channel based on Amplify-and-Forward Multi-relaying Systems

This paper analyzes the cascade channel estimation of Amplify-and-Forward (AF) multi-relaying systems. To improve the accuracy, a maximum a posteriori (MAP) estimator is obtained with the prior probability distribution function (PDF) of the cascade channel. For lessening the computational amount of...

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Bibliographic Details
Published inProcedia computer science Vol. 34; pp. 15 - 22
Main Authors Liu, Haibin, Ding, Hong, Yuan, Jibing, Zheng, Linhua, Wang, Shuai
Format Journal Article
LanguageEnglish
Published Elsevier B.V 2014
Subjects
Amplify-and-Forward (AF)
bayesian theory
cascade channel estimation
multi-relaying
cascade channel estimation
multi-relaying
Amplify-and-Forward (AF)
bayesian theory
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Summary:This paper analyzes the cascade channel estimation of Amplify-and-Forward (AF) multi-relaying systems. To improve the accuracy, a maximum a posteriori (MAP) estimator is obtained with the prior probability distribution function (PDF) of the cascade channel. For lessening the computational amount of the MAP method, the complicated generalized-K distribution is approximated with a Gamma PDF based on the moment-matching method. Moreover, a closed-form and simplified MAP (sMAP) estimator is derived. Numerical simulation shows that the proposed sMAP estimator decreases the computational duration sharply than the MAP method with marginal performance loss, and outperforms its least square (LS) counterpart in the low SNR region.
ISSN:1877-0509
1877-0509
DOI:10.1016/j.procs.2014.07.008