NDLI: Segment Training Based Individual Channel Estimation in One-Way Relay Network with Power Allocation

Content Provider	IEEE Xplore Digital Library
Author	Shun Zhang Feifei Gao Changxing Pei Xiandeng He
Copyright Year	2002
Abstract	In this paper, we design a segment training based individual channel estimation (STICE) scheme in the classical three-node it amplify-and-forward (AF) one-way relay network (OWRN). The linear minimum mean-square-error (LMMSE) channel estimator is used to obtain a good initialization, and an iterative maximum a posteriori (MAP) channel estimator is developed to improve the estimation accuracy. We then investigate the underlying power allocation at the relay node both to minimize the mean-square-error (MSE) of the individual channel estimation and to maximize the average effective signal-to-noise ratio (AESNR) of the data detection. The closed-form Bayesian Cramér-Rao Bound (CRB) is also derived to evaluate the proposed algorithm. Finally, numerical results are provided to corroborate the proposed studies.
Starting Page	1300
Ending Page	1309
Page Count	10
File Size	663179
File Format	PDF
ISSN	15361276
Volume Number	12
Issue Number	3
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Relays Estimation Channel estimation Training Resource management Vectors Bayesian methods maximum a posteriori Individual channel estimation one-way relay Cram'er-Rao Bound power allocation
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Electrical and Electronic Engineering Computer Science Applications

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