Mobile Charging in Wireless-Powered Sensor Networks: Optimal Scheduling and Experimental Implementation

Wireless radio frequency (RF) energy transfer is a promising technology to provide a reliability-guaranteed power supply for wireless sensor networks. In this paper, we consider a special wireless-powered sensor network consisting of a mobile energy station that can travel through a preplanned path...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on vehicular technology 2017-08, Vol.66 (8), p.7400-7410
Main Authors: Sangare, Fahira, Yong Xiao, Niyato, Dusit, Zhu Han
Format: Article
Language:English
Subjects:
Energy harvesting
Energy transfer
Hardware
Markov decision process
Mathematical models
mobile charging
Mobile communication
Mobile computing
Network reliability
Optimization
Path planning
Performance enhancement
Power supplies
Radio frequency
Remote sensors
Robot sensing systems
Scheduling
sensor networks
Sensors
Technology transfer
wireless power transfer
Wireless sensor networks
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Wireless radio frequency (RF) energy transfer is a promising technology to provide a reliability-guaranteed power supply for wireless sensor networks. In this paper, we consider a special wireless-powered sensor network consisting of a mobile energy station that can travel through a preplanned path to charge wireless-powered sensors located in the considered area. We develop a hardware platform using off-the-shelf RF energy transfer hardware equipment to evaluate the practical performance of wireless sensor networks powered by RF energy transfer. We establish an empirical model based on our developed platform and use the empirical model to jointly optimize path planning and mobile charge scheduling for wireless-powered sensor networks. We derive the optimal policy for the mobile energy station to optimize its decisions about the path that it will travel and the subset of sensors to charge during each time period. Numerical results show that our derived policy significantly improves the performance of wireless sensor networks in different practical scenarios.
ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2017.2668990