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Published in: The Journal of Supercomputing 12/2018

24-02-2018

Multi-objective optimization design for multi-source multicasting MIMO AF relay systems

Authors: Min Zhu, Dengyin Zhang, Jin Wang

Published in: The Journal of Supercomputing | Issue 12/2018

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Abstract

In this paper, we consider a multi-source multicasting two-hop multi-input multi-output amplify-forward (AF) relay system, where multiple source nodes multicast their own messages to a group of receivers with the cooperation of an AF relay node. In particular, we aim at minimizing the transmission power consumption and the mean-squared error (MSE) of the receiver estimated signal simultaneously. However, the two objectives are coupled and even conflicting. In view of this, a multi-objective optimization (MOO) framework is adopted to achieve the trade-off between the two objectives. The formulated MOO problem (MOOP) takes into account the constraints of the MSE upper bound and the maximum transmission power budget. Since the MOOP is non-convex and hard to tackle, we propose a resource allocation algorithm by exploiting the weighted Tchebycheff approach and the optimal structure of the relay precoding matrix. Simulation results not only demonstrate the effectiveness of the proposed algorithm, but also unveil an important trade-off between the total power consumption and the MSE at receivers.

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Appendix
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Metadata
Title
Multi-objective optimization design for multi-source multicasting MIMO AF relay systems
Authors
Min Zhu
Dengyin Zhang
Jin Wang
Publication date
24-02-2018
Publisher
Springer US
Published in
The Journal of Supercomputing / Issue 12/2018
Print ISSN: 0920-8542
Electronic ISSN: 1573-0484
DOI
https://doi.org/10.1007/s11227-018-2275-z

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