Energy efficient 3D positioning of micro unmanned aerial vehicles for underlay cognitive radio systems

Micro unmanned aerial vehicles (MUAVs) have attracted much interest as flexible communication means for multiple applications due to their versatility. Most of the MUAV-based applications require a time-limited access to the spectrum to complete data transmission due to limited battery capacity of the flying units. These characteristics are the origin of two main challenges faced by MUAV-based communication: 1) efficient-energy management, and 2) opportunistic spectrum access. This paper proposes an energy-efficient solution, considering the hover and communication energy, to address these issues by integrating cognitive radio (CR) technology with MUAVs. A non-convex optimization problem exploiting the mobility of MUAVs is developed for the underlay CR technique. The objective is to determine an optimized three-dimension (3D) location, for a secondary MUAV, at which it can complete its data transfer with minimum energy consumption and without harming the data rate requirement of the primary spectrum owner. Two algorithms are proposed to solve these optimization problems: a meta-heuristic particle swarm optimization algorithm (PSO) and a deterministic algorithm based on Weber formulation. Selected numerical results show the behavior of the MUAV versus various system parameters and that the proposed solutions achieve very close results in spite of the different conceptional constructions.