Energy Efficiency Optimization for UAV-assisted mMTC Networks with Altitude Differences

With the increase of the number of intelligent users, massive machine-type communications (mMTC), which can accommodate massive users, will play an important role. Unmanned aerial vehicle (UAV) has attracted a lot of attention due to the high mobility. However, both machine-type communications devices (MTCDs) and UAVs are battery-powered, therefore they have limited energy storage. In this paper, we focus on energy efficiency optimization in UAV-assisted mMTC networks with altitude differences. Considering the altitude differences of MTCDs, the Euclidean distances between MTCDs are in three dimensions. Besides, the altitudes of clustering centers are different, which results in the different altitudes of the hovering positions. To optimize the energy efficiency of MTCDs, a hovering positions selection algorithm based on three-dimensional clustering (3D-HPSA) is proposed. Meanwhile, a Discrete Cuckoo Search Algorithm with Genetic Mutation Operators (GMO-DCSA) is proposed to optimize the flight distance and the energy efficiency of UAV. Simulation results show that the proposed algorithms have superior performances compared with the existing works.