Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/150423
Title: Robust transmissions in wireless powered multi-relay networks with chance interference constraint
Authors: Xu, Jing
Zou, Yuze
Gong, Shimin
Gao, Lin
Niyato, Dusit
Cheng, Wenqing
Keywords: Engineering::Computer science and engineering
Issue Date: 2018
Source: Xu, J., Zou, Y., Gong, S., Gao, L., Niyato, D. & Cheng, W. (2018). Robust transmissions in wireless powered multi-relay networks with chance interference constraint. IEEE Transactions On Communications, 67(2), 973-987. https://dx.doi.org/10.1109/TCOMM.2018.2877466
Project: 2017-T1-002-007 RG122/17
MOE2014-T2-2-015 ARC4/15
NRF2015-NRF-ISF001-2277
Journal: IEEE Transactions on Communications
Abstract: In this paper, we consider a wireless powered multi-relay network in which a multi-antenna hybrid access point underlaying a cellular system transmits information to distant receivers. Multiple relays capable of energy harvesting are deployed in the network to assist the information transmission. The hybrid access point can wirelessly supply energy to the relays, achieving multi-user gains from signal and energy cooperation. We propose a joint optimization for signal beamforming of the hybrid access point as well as wireless energy harvesting and collaborative beamforming strategies of the relays. The objective is to maximize network throughput subject to probabilistic interference constraints at the cellular user equipment. We formulate the throughput maximization with both the time-switching and power-splitting schemes, which impose very different couplings between the operating parameters for wireless power and information transfer. Although the optimization problems are inherently non-convex, they share similar structural properties that can be leveraged for efficient algorithm design. In particular, by exploiting monotonicity in the throughput, we maximize it iteratively via customized polyblock approximation with reduced complexity. The numerical results show that the proposed algorithms can achieve close to optimal performance in terms of the energy efficiency and throughput.
URI: https://hdl.handle.net/10356/150423
ISSN: 0090-6778
DOI: 10.1109/TCOMM.2018.2877466
Rights: © 2018 IEEE. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Journal Articles

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