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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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2017
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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. |
format | Online Article Text |
id | pubmed-5375833 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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