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Energy and Information Beamforming in Airborne Massive MIMO System for Wireless Powered Communications

Energy supply and information backhaul are critical problems for wireless sensor networks deployed in remote places with poor infrastructure. To deal with these problems, this paper proposes an airborne massive multiple-input multiple-output (MIMO) system for wireless energy transfer (WET) and infor...

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Autores principales: Wang, Yurong, Liu, Aijun, Xu, Kui, Xia, Xiaochen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6210597/
https://www.ncbi.nlm.nih.gov/pubmed/30347714
http://dx.doi.org/10.3390/s18103540
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author Wang, Yurong
Liu, Aijun
Xu, Kui
Xia, Xiaochen
author_facet Wang, Yurong
Liu, Aijun
Xu, Kui
Xia, Xiaochen
author_sort Wang, Yurong
collection PubMed
description Energy supply and information backhaul are critical problems for wireless sensor networks deployed in remote places with poor infrastructure. To deal with these problems, this paper proposes an airborne massive multiple-input multiple-output (MIMO) system for wireless energy transfer (WET) and information transmission. An air platform (AP) equipped with a two-dimensional rectangular antenna array is employed to broadcast energy and provide wireless access for ground sensors. By exploiting the statistical property of air-terrestrial MIMO channels, the energy and information beamformers are jointly designed to maximize the average received signal-to-interference-plus-noise ratio (SINR), which gives rise to a statistical max-SINR beamforming scheme. The scheme does not rely on the instantaneous channel state information, but still requires large numbers of RF chains at AP. To deal with this problem, a heuristic strongest-path energy and information beamforming scheme is proposed, which can be implemented in the analog-domain with low computational and hardware complexity. The analysis of the relation between the two schemes reveals that, with proper sensor scheduling, the strongest-path beamforming is equivalent to the statistical max-SINR beamforming when the number of AP antennas tends to infinity. Using the asymptotic approximation of average received SINR at AP, the system parameters, including transmit power, number of active antennas of AP and duration of WET phase, are optimized jointly to maximize the system energy efficiency. The simulation results demonstrate that the proposed schemes achieve a good tradeoff between system performance and complexity.
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spelling pubmed-62105972018-11-02 Energy and Information Beamforming in Airborne Massive MIMO System for Wireless Powered Communications Wang, Yurong Liu, Aijun Xu, Kui Xia, Xiaochen Sensors (Basel) Article Energy supply and information backhaul are critical problems for wireless sensor networks deployed in remote places with poor infrastructure. To deal with these problems, this paper proposes an airborne massive multiple-input multiple-output (MIMO) system for wireless energy transfer (WET) and information transmission. An air platform (AP) equipped with a two-dimensional rectangular antenna array is employed to broadcast energy and provide wireless access for ground sensors. By exploiting the statistical property of air-terrestrial MIMO channels, the energy and information beamformers are jointly designed to maximize the average received signal-to-interference-plus-noise ratio (SINR), which gives rise to a statistical max-SINR beamforming scheme. The scheme does not rely on the instantaneous channel state information, but still requires large numbers of RF chains at AP. To deal with this problem, a heuristic strongest-path energy and information beamforming scheme is proposed, which can be implemented in the analog-domain with low computational and hardware complexity. The analysis of the relation between the two schemes reveals that, with proper sensor scheduling, the strongest-path beamforming is equivalent to the statistical max-SINR beamforming when the number of AP antennas tends to infinity. Using the asymptotic approximation of average received SINR at AP, the system parameters, including transmit power, number of active antennas of AP and duration of WET phase, are optimized jointly to maximize the system energy efficiency. The simulation results demonstrate that the proposed schemes achieve a good tradeoff between system performance and complexity. MDPI 2018-10-19 /pmc/articles/PMC6210597/ /pubmed/30347714 http://dx.doi.org/10.3390/s18103540 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Wang, Yurong
Liu, Aijun
Xu, Kui
Xia, Xiaochen
Energy and Information Beamforming in Airborne Massive MIMO System for Wireless Powered Communications
title Energy and Information Beamforming in Airborne Massive MIMO System for Wireless Powered Communications
title_full Energy and Information Beamforming in Airborne Massive MIMO System for Wireless Powered Communications
title_fullStr Energy and Information Beamforming in Airborne Massive MIMO System for Wireless Powered Communications
title_full_unstemmed Energy and Information Beamforming in Airborne Massive MIMO System for Wireless Powered Communications
title_short Energy and Information Beamforming in Airborne Massive MIMO System for Wireless Powered Communications
title_sort energy and information beamforming in airborne massive mimo system for wireless powered communications
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6210597/
https://www.ncbi.nlm.nih.gov/pubmed/30347714
http://dx.doi.org/10.3390/s18103540
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