Energy-Efficient Management of Unmanned Aerial Vehicles for Underlay Cognitive Radio Systems

Micro unmanned aerial vehicles (MUAVs) have attracted much interest in multiple applications. Most of the MUAV-based applications require 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 challenges in MUAV-based communications: 1) efficient-energy management and 2) opportunistic spectrum access. This paper proposes an energy-efficient solution to minimize the MUAV’s flying and communication energies while integrating cognitive radio technology. A non-convex optimization problem exploiting the mobility of MUAVs is developed for the underlay operating mode where the data rate threshold of the spectrum’s owner has to be respected. The objective is to determine a joint optimized 3-D location and transmit power control solution by which the secondary MUAV can complete its transmission. A deterministic algorithm based on the Weber formulation is proposed to solve the optimization problem. The performances of the deterministic approach are compared to those of a meta-heuristic algorithm, namely particle swarm optimization algorithm (PSO). Selected numerical results illustrate the behavior of the MUAV versus various system parameters. It is shown that the proposed solution achieves very close results to those of the PSO in spite of their different conceptional constructions.