FlyingLoRa: Towards energy efficient data collection in UAV-assisted LoRa networks

Energy efficiency is an increasingly crucial consideration due to the battery-powered end devices in LoRa networks. With the adoption of chirp spread spectrum modulation, end devices far apart from the gateway have to use a high spreading factor and transmit power to send uplink packets, which causes longer transmission time and higher energy consumption compared to the end devices near the gateway, and further causes unfairness issues on energy efficiency. To tackle this problem, we investigate a novel energy-efficient data collection scheme named FlyingLoRa, where an unmanned aerial vehicle carrying one gateway is dispatched to harvest packets from end devices. The goal of FlyingLoRa is to minimize the energy consumption of end devices for packet transmission by jointly optimizing the 3D UAV trajectory, scheduling strategies, and transmission parameters of end devices. We formulate our design as a mixed-integer non-convex optimization problem and propose an efficient iterative algorithm to find a sub-optimal solution. The proposed approach is numerically simulated and the results show that FlyingLoRa improves energy efficiency by 16.13x on average compared with the existing fixed gateway schemes. In addition, we realize FlyingLoRa in real scenarios and evaluate its performance by presenting the actual packet reception rate (PRR) and transmission energy consumption, which shows its effectiveness.