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Optimal Power Control in Wireless Powered Sensor Networks: A Dynamic Game-Based Approach

In wireless powered sensor networks (WPSN), it is essential to research uplink transmit power control in order to achieve throughput performance balancing and energy scheduling. Each sensor should have an optimal transmit power level for revenue maximization. In this paper, we discuss a dynamic game...

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Detalles Bibliográficos
Autores principales: Xu, Haitao, Guo, Chao, Zhang, Long
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5375833/
https://www.ncbi.nlm.nih.gov/pubmed/28282945
http://dx.doi.org/10.3390/s17030547
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author Xu, Haitao
Guo, Chao
Zhang, Long
author_facet Xu, Haitao
Guo, Chao
Zhang, Long
author_sort Xu, Haitao
collection PubMed
description In wireless powered sensor networks (WPSN), it is essential to research uplink transmit power control in order to achieve throughput performance balancing and energy scheduling. Each sensor should have an optimal transmit power level for revenue maximization. In this paper, we discuss a dynamic game-based algorithm for optimal power control in WPSN. The main idea is to use the non-cooperative differential game to control the uplink transmit power of wireless sensors in WPSN, to extend their working hours and to meet QoS (Quality of Services) requirements. Subsequently, the Nash equilibrium solutions are obtained through Bellman dynamic programming. At the same time, an uplink power control algorithm is proposed in a distributed manner. Through numerical simulations, we demonstrate that our algorithm can obtain optimal power control and reach convergence for an infinite horizon.
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spelling pubmed-53758332017-04-10 Optimal Power Control in Wireless Powered Sensor Networks: A Dynamic Game-Based Approach Xu, Haitao Guo, Chao Zhang, Long Sensors (Basel) Article In wireless powered sensor networks (WPSN), it is essential to research uplink transmit power control in order to achieve throughput performance balancing and energy scheduling. Each sensor should have an optimal transmit power level for revenue maximization. In this paper, we discuss a dynamic game-based algorithm for optimal power control in WPSN. The main idea is to use the non-cooperative differential game to control the uplink transmit power of wireless sensors in WPSN, to extend their working hours and to meet QoS (Quality of Services) requirements. Subsequently, the Nash equilibrium solutions are obtained through Bellman dynamic programming. At the same time, an uplink power control algorithm is proposed in a distributed manner. Through numerical simulations, we demonstrate that our algorithm can obtain optimal power control and reach convergence for an infinite horizon. MDPI 2017-03-09 /pmc/articles/PMC5375833/ /pubmed/28282945 http://dx.doi.org/10.3390/s17030547 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
Xu, Haitao
Guo, Chao
Zhang, Long
Optimal Power Control in Wireless Powered Sensor Networks: A Dynamic Game-Based Approach
title Optimal Power Control in Wireless Powered Sensor Networks: A Dynamic Game-Based Approach
title_full Optimal Power Control in Wireless Powered Sensor Networks: A Dynamic Game-Based Approach
title_fullStr Optimal Power Control in Wireless Powered Sensor Networks: A Dynamic Game-Based Approach
title_full_unstemmed Optimal Power Control in Wireless Powered Sensor Networks: A Dynamic Game-Based Approach
title_short Optimal Power Control in Wireless Powered Sensor Networks: A Dynamic Game-Based Approach
title_sort optimal power control in wireless powered sensor networks: a dynamic game-based approach
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5375833/
https://www.ncbi.nlm.nih.gov/pubmed/28282945
http://dx.doi.org/10.3390/s17030547
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