TY - JOUR
T1 - Wireless Power Transmitter Deployment for Balancing Fairness and Charging Service Quality
AU - Liu, Mingqing
AU - Wang, Gang
AU - Giannakis, Georgios B.
AU - Xiong, Mingliang
AU - Liu, Qingwen
AU - Deng, Hao
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2020/3
Y1 - 2020/3
N2 - Wireless energy transfer (WET) has recently emerged as an appealing solution for power supplying mobile/Internet of Things (IoT) devices. As an enabling WET technology, resonant beam charging (RBC) is well documented for its long-range, high-power, and safe 'WiFi-like' mobile power supply. To provide high-quality wireless charging services for multiple users in a given region, we formulate a deployment problem of multiple RBC transmitters for balancing the charging fairness and quality of charging service. Based on the RBC transmitter's coverage model and receiver's charging/discharging model, a genetic algorithm (GA)-based scheme and a particle swarm optimization (PSO)-based scheme are put forth to resolve the above issue. Moreover, we present a scheduling method to evaluate the performance of the proposed algorithms. The numerical results corroborate that the optimized deployment schemes outperform uniform and random deployment in 10%-20% charging efficiency improvement.
AB - Wireless energy transfer (WET) has recently emerged as an appealing solution for power supplying mobile/Internet of Things (IoT) devices. As an enabling WET technology, resonant beam charging (RBC) is well documented for its long-range, high-power, and safe 'WiFi-like' mobile power supply. To provide high-quality wireless charging services for multiple users in a given region, we formulate a deployment problem of multiple RBC transmitters for balancing the charging fairness and quality of charging service. Based on the RBC transmitter's coverage model and receiver's charging/discharging model, a genetic algorithm (GA)-based scheme and a particle swarm optimization (PSO)-based scheme are put forth to resolve the above issue. Moreover, we present a scheduling method to evaluate the performance of the proposed algorithms. The numerical results corroborate that the optimized deployment schemes outperform uniform and random deployment in 10%-20% charging efficiency improvement.
KW - Internet of Things (IoT)
KW - mobile energy transfer
KW - resonant beam charging (RBC)
KW - transmitter deployment
UR - http://www.scopus.com/inward/record.url?scp=85082136542&partnerID=8YFLogxK
U2 - 10.1109/JIOT.2019.2958660
DO - 10.1109/JIOT.2019.2958660
M3 - Article
AN - SCOPUS:85082136542
SN - 2327-4662
VL - 7
SP - 2223
EP - 2234
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
IS - 3
M1 - 8930494
ER -