An intelligent age of information based self-energized UAV-assisted wireless communication system

Internet-of-things is an enabling technology in the fourth-generation industrial revolution. The freshness of the data sent by a sensor node (SN) is an important parameter in the Internet-of-things, unlike the throughput in cellular communications. A relatively new performance metric named age of information (AoI) is used in this paper to quantify the freshness of the data. The SN, located in the transport infrastructure, harvests energy from radio frequency signals transmitted by the FD-UAV. This is used to transmit real-time sensor observations to the data sink via FD-UAV. The SN generates an update after replenishing the battery and transmits it by using the harvested energy. A closed-form expression for average AoI is derived as a function of time allocated for energy harvesting. The optimal time allocation for energy harvesting that maximizes the freshness of data update is identified. A deep learning technique namely long-short term memory is used to predict the average AoI. Simulation results demonstrate the usefulness of the performance bounds in terms of the freshness of data updates.