无线电源传输
无线
计算机科学
粒子群优化
可穿戴计算机
启发式
贪婪算法
数学优化
实时计算
电气工程
工程类
嵌入式系统
算法
电信
数学
人工智能
作者
Yanjun Li,Chung Shue Chen,Chung Shue Chen,Zhibo Wang,Yi‐hua Zhu
出处
期刊:IEEE Transactions on Vehicular Technology
[Institute of Electrical and Electronics Engineers]
日期:2018-09-24
卷期号:67 (12): 11575-11586
被引量:32
标识
DOI:10.1109/tvt.2018.2871870
摘要
With the promising technology of far-field wireless power transfer, wearable devices are able to harvest radio frequency (RF) energy from RF-based chargers and thus operate continuously. Rational planning of the quantity and positions of the chargers provide an effective way to improve the recharging efficiency and save the charger deployment budget. Existing work on RF-based charger placement mainly considers the situation where the devices are static, or adopt very simple mobility model. In this paper, we consider wireless charging service provision for wearable devices worn by users in a two-dimensional area, with users having a specific stay-move behavior pattern characterized by the trajectories, stay points, and stay time distribution. Based on this mobility pattern, we formulate the problem as how to find a charger placement to minimize the charging service budget, subject to the power non-outage probability requirement of the wearable devices. We further transform this problem to several equivalent problems for easier tractability and prove that it is NP-complete. Both greedy heuristic and particle swarm optimization (PSO) based solutions are proposed to solve the problem with certain approximation ratio. Finally, performances of the proposed solutions are compared with exhaustive search and existing point provisioning algorithm through extensive simulations. Simulation results show that both greedy heuristic and PSO-based solutions outperform the baseline algorithms, while PSO-based solution requires least number of chargers and thus is the most cost-effective.
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