Distributed Charging Control in Broadband Wireless Power Transfer Networks
Suzhi Bi, Rui Zhang
备注：
This paper has been accepted for publication in Journal on Selected Areas in Communications - Series on Communications and Networking (Dec. 2016 issue)
Wireless power transfer (WPT) technology provides a cost-effective solution to achieve sustainable energy supply in wireless networks, where WPT-enabled energy nodes (ENs) can charge wireless devices (WDs) remotely without interruption to the use. However, in a heterogeneous WPT network with distributed ENs and WDs, some WDs may quickly deplete their batteries due to the lack of timely wireless power supply by the ENs, thus resulting in short network operating lifetime. In this paper, we exploit frequency diversity in a broadband WPT network and study the distributed charging control by ENs to maximize network lifetime. In particular, we propose a practical voting-based distributed charging control framework where each WD simply estimates the broadband channel, casts its vote(s) for some strong sub-channel(s) and sends to the ENs along with its battery state information, based on which the ENs independently allocate their transmit power over the sub-channels without the need of centralized control. Under this framework, we aim to design lifetime-maximizing power allocation and efficient voting-based feedback methods. Towards this end, we first derive the general expression of the expected lifetime of a WPT network and draw the general design principles for lifetime-maximizing charging control. Based on the analysis, we then propose a distributed charging control protocol with voting-based feedback, where the power allocated to sub-channels at each EN is a function of the weighted sum vote received from all WDs. Besides, the number of votes cast by a WD and the weight of each vote are related to its current battery state. Simulation results show that the proposed distributed charging control protocol could significantly increase the network lifetime under stringent transmit power constraint in a broadband WPT network.
Recent advances in wireless power transfer (WPT) technology provide a cost-effective solution to charge wireless devices remotely without disruption to the use. In this paper, we propose an efficient wireless charging control method for exploiting the frequency diversity in multiuser broadband wireless networks, to reduce energy outage and keep the system operating in an efficient and sustainable state. In particular, we first analyze the impact of charging control method to the operating lifetime of a WPT-enabled broadband system. Based on the analysis, we then propose a multi-criteria chargi…
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Huaqiao University（华侨大学）；Key Laboratory of Computer Vision and Machine Learning(Huaqiao University), Fujian Province University（福建省高校计算机视觉与机器学习重点实验室）；Central South University of Forestry and Technology（中南林业科技大学）；Yuan Ze University（中原大学）
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Wireless charging is a technique of transmitting power through an air gap to an electrical device for the purpose of energy replenishment. Recently, the wireless charging technology has been significantly advanced in terms of efficiency and functionality. This article first presents an overview and fundamentals of wireless charging. We then provide the review of standards, i.e., Qi and Alliance for Wireless Power (A4WP), and highlight on their communication protocols. Next, we propose a novel concept of wireless charger networking which allows chargers to be connected to facilitate information…
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Hangzhou International Innovation Institute of Beihang University（北京航空航天大学杭州创新研究院）；School of Automation Science and Electrical Engineering at Beihang University（北京航空航天大学自动化科学与电气工程学院）；State Key Laboratory of Intelligent Manufacturing Systems Technology（智能制造系统技术国家重点实验室）；Department of Computer Science and Engineering, University of Bologna（博洛尼亚大学计算机科学与工程系）；Department of Computer Science and Information Technology, College of Engineering, Abu Dhabi University（阿布扎比大学工程学院计算机科学与技术系）；Department of Software Engineering, Faculty of Engineering and Architecture, Nisantasi University（尼桑塔西大学工程与建筑学院软件工程系）；School of Artificial Intelligence, Shenzhen University（深圳大学人工智能学院）；School of Information Engineering, Guangdong University of Technology（广东工业大学信息工程学院）
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College of Computer Science and Technology, Jilin University（吉林大学计算机科学与技术学院）；Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University（吉林大学符号计算与知识工程教育部重点实验室）
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