Smart 6G Sky for Green Mobile IOT Networks

6G is envisioned to connect everything and yet to be a hundred times more energy efficient than the 5G. Thanks for its ability to use sources of ambient energy, energy harvesting (EH) is promising in alleviating the challenge of meeting such conflicting demands. Moreover, when it comes to the Internet of things (IoT), one of the foundations for enabling connecting everything, the need for EH may become inevitable. IoT involves connecting not only devices that are large in number, but also hard to reach. The good news, nevertheless, is that the unmanned aerial vehicle (UAV), owning to its flexibility and ease of deployment is emerging to offer communication services when infrastructure is lacking. Merging the UAV and IoT is of quite interest as the former could not just enable flexible connectivity for the IoT but also powering them in spite of any restrictions. However, managing the UAV assisted IoT resources to meet certain data communications and EH quality measures while keeping the UAV consumed energy minimized is a major challenge as this corresponds to a non-convex optimization problem. Things, obviously, become even worse when the IoT network devices are mobile. Owing to the success of artificial intelligence (AI) in solving complicated problems, in this project we rely on the deep deterministic policy gradient (DDPG) technique, to manage the UAV assisted IoT resources. Our results show that DDPG achieves joint optimization of three objectives, namely sum data rate and harvested energy maximization, and energy consumption minimization, while out performing traditional mathematical schemes. The code of this project is made publicly accessible at https://github.com/QusaiBshiwa/Smart-6G- Sky-for-Green-Mobile-IOT-Networks