Multi-Criterion Resource Management in Energy Harvested Cooperative UAV-enabled IoT Networks

Cooperative communication by employing unmanned aerial vehicle (UAV)-based relays with RF energy harvesting (EH) has been emerged as a prominent solution to provide extended coverage, connectivity, capacity, energy efficiency, and reliability in the future Internet of things (IoT) systems. For successful integration of UAV relays in IoT networks, efficient radio resource management (RRM) is critical. We developed a multi-criterion framework for energy-efficient RRM in a cooperative IoT network. We considered UAVs as relays, onboard EH facilities and deployed to relay the messages from a satellite terminal to the network IoT devices. We adopted a power splitting (PS)-based EH scheme, i.e, PS relaying protocol, for RF-EH at UAV relays. We formulate a joint optimization problem for IoT device selection, UAV relay assignment, source power allocation, and PS ratio selection. In our multi-criterion framework, we consider three conflicting objectives by applying a weighted sum method: maximizing the network sum rate, maximizing the number of IoT devices to be served, and minimizing the carbon dioxide emissions. We propose an outer approximation algorithm (OAA) to solve the formulated problem which is a mixed-integer non-linear programming (MINLP) problem. Simulation results of the proposed algorithm are compared with two existing solutions, namely, the non-linear optimization by mesh adaptive direct search (NOMAD) algorithm and an evolutionary algorithm (EA). The performance of the NOMAD algorithm is better in terms of computational complexity. However, the simulation results reveal the supremacy of the proposed OAA in terms of network sum rate, the number of selected IoT devices, and network utility.