Data Gathering and Energy Transfer Dilemma in UAV-Assisted Flying Access Network for IoT

• Main Authors: Sara Arabi, Essaid Sabir, Halima Elbiaze, Mohamed Sadik
• Format: Article
• Language: English
• Published: MDPI AG 2018-05-01
• Series: Sensors
• Subjects: unmanned aerial vehicle (UAV); Internet-of-Things; energy harvesting; data collection; wireless recharging; scheduling time; UAV trajectory planning
• Online Access: http://www.mdpi.com/1424-8220/18/5/1519

Recently, Unmanned Aerial Vehicles (UAVs) have emerged as an alternative solution to assist wireless networks, thanks to numerous advantages they offer in comparison to terrestrial fixed base stations. For instance, a UAV can be used to embed a flying base station providing an on-demand nomadic access to network services. A UAV can also be used to wirelessly recharge out-of-battery ground devices. In this paper, we aim to deal with both data collection and recharging depleted ground Internet-of-Things (IoT) devices through a UAV station used as a flying base station. To extend the network lifetime, we present a novel use of UAV with energy harvesting module and wireless recharging capabilities. However, the UAV is used as an energy source to empower depleted IoT devices. On one hand, the UAV charges depleted ground IoT devices under three policies: (1) low-battery first scheme; (2) high-battery first scheme; and (3) random scheme. On the other hand, the UAV station collects data from IoT devices that have sufficient energy to transmit their packets, and in the same phase, the UAV exploits the Radio Frequency (RF) signals transmitted by IoT devices to extract and harvest energy. Furthermore, and as the UAV station has a limited coverage time due to its energy constraints, we propose and investigate an efficient trade-off between ground users recharging time and data gathering time. Furthermore, we suggest to control and optimize the UAV trajectory in order to complete its travel within a minimum time, while minimizing the energy spent and/or enhancing the network lifetime. Extensive numerical results and simulations show how the system behaves under different scenarios and using various metrics in which we examine the added value of UAV with energy harvesting module.