UAV-aided Sustainable Communication in Cellular IoT System with Hybrid Energy Harvesting

Green communication in smart city, where Internet of Things (IoT) applications are extensively deployed, is a great concern of 5G cellular network design. In this paper, we adopt Ginibre Determinant Point Process to characterize distribution of machine type communication gateways in a single cellular coverage. Drone-based access point is introduced to establish favorable wireless channel. We then establish a large-scale linear programming problem to find the minimum electric power consumption of the IoT system where ambient radio and on-chip battery are the sole energy sources. Specifically, a hybrid energy harvesting protocol combining millimeter wave and microwave below 6GHz is presented to enhance system sustainability. Two typical energy harvesting modes are proposed, of which the first mode performs better when dealing with long-term Machine-to-Machine (M2M) communication service, while the second mode is more suited to occasional short-term energy sharing. When machine type communication device is abundantly charged at the beginning, we further obtain the closed-form expression revealing the ratio relationship between average electric power consumption under both modes, which is explicitly related to: (a) initial battery energy level of machine type network nodes, (b) service-oriented hybrid energy harvest (EH) protocol configuration, (c) system operation time and (4) fundamental electric and battery consumption of the whole system. Extensive experiments are conducted using rejection sampling method and interior-point method through MATLAB simulation.