A WPT-Enabled UAV-Assisted Condition Monitoring Scheme for Wireless Sensor Networks

• Published in: IEEE transactions on intelligent transportation systems Vol. 22; no. 8; pp. 5112 - 5126
• Main Authors: Ponnimbaduge Perera, Tharindu Dilshan, Panic, Stefan, Jayakody, Dushantha Nalin K., Muthuchidambaranathan, P., Li, Jun
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-08-2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Asymptotic methods; Complexity; Condition monitoring; Energy harvesting; Heuristic methods; Optimization; Power system reliability; Probability; Radio frequency; Remote sensors; Resource allocation; Resource management; RF energy harvesting; RF wireless power transfer; Sensors; UAV communication; Unmanned aerial vehicles; Wireless communication; Wireless networks; Wireless power transmission; Wireless sensor networks; wireless sensor networks and 5G communication
• ISSN: 1524-9050; 1558-0016
• DOI: 10.1109/TITS.2020.3018493

In this paper, a resource allocation and data gathering scenario of an unmanned aerial vehicle (UAV) assisted wireless powered sensor network is investigated, in which the sensor nodes (SNs) are remotely powered by power beacons (PBs) via radio-frequency wireless power transmission (RF-WPT). A time-block structure with two phases is proposed to accommodate operations in the proposed system. During Phase-I, SNs harvest energy from PBs and periodically send its sensed data to the selected cluster heads (CHs). In Phase-II, an UAV collects the data from CHs to be delivered to the data sink for further processing avoiding the need for long range transmission and multi hop communication to the data sink. Then, a closed-form expression for outage probability of the proposed system over Rayleigh and Rician fading channels is derived. Next, outage probability minimization problem is formulated to obtain optimal time allocation for RF-WPT energy harvesting to improve the system performance. Due to the complexity of the problem, Lagrangian duality method is used to develop an asymptotic optimal solution with less execution complexity avoiding complex brute force/ exhaustive search approach. Furthermore, a heuristic method is presented to further lower the computation complexity. Simulation results reveal the superiority of the proposed methods compare to brute force/ exhaustive search approach via analysis, comparison and insights of the system performance results. Finally, the performance superiority of the proposed system is demonstrated with compare to identified baseline WSNs.