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Energy Efficiency Maximization for WSNs with Simultaneous Wireless Information and Power Transfer

Recently, the simultaneous wireless information and power transfer (SWIPT) technique has been regarded as a promising approach to enhance performance of wireless sensor networks with limited energy supply. However, from a green communication perspective, energy efficiency optimization for SWIPT syst...

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Autores principales: Yu, Hongyan, Zhang, Yongqiang, Guo, Songtao, Yang, Yuanyuan, Ji, Luyue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5579579/
https://www.ncbi.nlm.nih.gov/pubmed/28820496
http://dx.doi.org/10.3390/s17081906
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author Yu, Hongyan
Zhang, Yongqiang
Guo, Songtao
Yang, Yuanyuan
Ji, Luyue
author_facet Yu, Hongyan
Zhang, Yongqiang
Guo, Songtao
Yang, Yuanyuan
Ji, Luyue
author_sort Yu, Hongyan
collection PubMed
description Recently, the simultaneous wireless information and power transfer (SWIPT) technique has been regarded as a promising approach to enhance performance of wireless sensor networks with limited energy supply. However, from a green communication perspective, energy efficiency optimization for SWIPT system design has not been investigated in Wireless Rechargeable Sensor Networks (WRSNs). In this paper, we consider the tradeoffs between energy efficiency and three factors including spectral efficiency, the transmit power and outage target rate for two different modes, i.e., power splitting (PS) and time switching modes (TS), at the receiver. Moreover, we formulate the energy efficiency maximization problem subject to the constraints of minimum Quality of Service (QoS), minimum harvested energy and maximum transmission power as non-convex optimization problem. In particular, we focus on optimizing power control and power allocation policy in PS and TS modes to maximize energy efficiency of data transmission. For PS and TS modes, we propose the corresponding algorithm to characterize a non-convex optimization problem that takes into account the circuit power consumption and the harvested energy. By exploiting nonlinear fractional programming and Lagrangian dual decomposition, we propose suboptimal iterative algorithms to obtain the solutions of non-convex optimization problems. Furthermore, we derive the outage probability and effective throughput from the scenarios that the transmitter does not or partially know the channel state information (CSI) of the receiver. Simulation results illustrate that the proposed optimal iterative algorithm can achieve optimal solutions within a small number of iterations and various tradeoffs between energy efficiency and spectral efficiency, transmit power and outage target rate, respectively.
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spelling pubmed-55795792017-09-06 Energy Efficiency Maximization for WSNs with Simultaneous Wireless Information and Power Transfer Yu, Hongyan Zhang, Yongqiang Guo, Songtao Yang, Yuanyuan Ji, Luyue Sensors (Basel) Article Recently, the simultaneous wireless information and power transfer (SWIPT) technique has been regarded as a promising approach to enhance performance of wireless sensor networks with limited energy supply. However, from a green communication perspective, energy efficiency optimization for SWIPT system design has not been investigated in Wireless Rechargeable Sensor Networks (WRSNs). In this paper, we consider the tradeoffs between energy efficiency and three factors including spectral efficiency, the transmit power and outage target rate for two different modes, i.e., power splitting (PS) and time switching modes (TS), at the receiver. Moreover, we formulate the energy efficiency maximization problem subject to the constraints of minimum Quality of Service (QoS), minimum harvested energy and maximum transmission power as non-convex optimization problem. In particular, we focus on optimizing power control and power allocation policy in PS and TS modes to maximize energy efficiency of data transmission. For PS and TS modes, we propose the corresponding algorithm to characterize a non-convex optimization problem that takes into account the circuit power consumption and the harvested energy. By exploiting nonlinear fractional programming and Lagrangian dual decomposition, we propose suboptimal iterative algorithms to obtain the solutions of non-convex optimization problems. Furthermore, we derive the outage probability and effective throughput from the scenarios that the transmitter does not or partially know the channel state information (CSI) of the receiver. Simulation results illustrate that the proposed optimal iterative algorithm can achieve optimal solutions within a small number of iterations and various tradeoffs between energy efficiency and spectral efficiency, transmit power and outage target rate, respectively. MDPI 2017-08-18 /pmc/articles/PMC5579579/ /pubmed/28820496 http://dx.doi.org/10.3390/s17081906 Text en © 2017 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
Yu, Hongyan
Zhang, Yongqiang
Guo, Songtao
Yang, Yuanyuan
Ji, Luyue
Energy Efficiency Maximization for WSNs with Simultaneous Wireless Information and Power Transfer
title Energy Efficiency Maximization for WSNs with Simultaneous Wireless Information and Power Transfer
title_full Energy Efficiency Maximization for WSNs with Simultaneous Wireless Information and Power Transfer
title_fullStr Energy Efficiency Maximization for WSNs with Simultaneous Wireless Information and Power Transfer
title_full_unstemmed Energy Efficiency Maximization for WSNs with Simultaneous Wireless Information and Power Transfer
title_short Energy Efficiency Maximization for WSNs with Simultaneous Wireless Information and Power Transfer
title_sort energy efficiency maximization for wsns with simultaneous wireless information and power transfer
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5579579/
https://www.ncbi.nlm.nih.gov/pubmed/28820496
http://dx.doi.org/10.3390/s17081906
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