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Open Access

Relay Selection Scheme for AF System with Partial CSI and Optimal Stopping Theory

School of Information Engineering, Xijing Institute, Xi’an 710123, China.
Beijing Institute of Information Engineering, Beijing 100085, China.
Institute of Information and Navigation, Air Force Engineering University, Xi’an 710008, China.
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Abstract

Relay selection for Relay Assisted (RA) networks is an economical and effective method to improve the spectrum efficiency. Relay selection performs especially well when the source node has accurate and timely Channel State Information (CSI). However, since perfect CSI knowledge is rarely available, research of relay selection with partial (statistical) CSI is of paramount importance. In this paper, relay selection for RA networks with statistical CSI is formulated as a Multiple-Decision (MD) problem. And, the cost of obtaining the CSI is also considered in the formulated problem. Two relay selection schemes, Maximal Selection Probability (MSP) and Maximal Spectrum Efficiency Expectation (MSEE), are proposed to solve the formulated MD problem under different optimal criteria assumptions based on the optimal stopping theory. The MSP scheme maximizes the probability that the Best Assisted Relay Candidate (BARC) can be selected, whereas the MSEE scheme provides the maximal expectation of the spectrum efficiency. Experimental results show that the proposed schemes effectively improve the spectrum efficiency, and the MSEE scheme is more suitable for stable communication cases. Meanwhile, the MSP scheme is more suitable for burst communication cases.

Keywords

Relay-Assisted (RA) networkrelay selectionoptimal stopping

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Tsinghua Science and Technology
Volume 25 Issue 2,
April 2020
Pages 302-312
DOI: 10.26599/TST.2019.9010001
Cite this article:
Zhu R, Li T, Guo J, et al. Relay Selection Scheme for AF System with Partial CSI and Optimal Stopping Theory. Tsinghua Science and Technology, 2020, 25(2): 302-312. https://doi.org/10.26599/TST.2019.9010001

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Received: 18 January 2019
Accepted: 19 January 2019
Published: 02 September 2019
© The author(s) 2020

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).
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