Abstract
Unmanned Aerial Vehicle (UAV) has been widely used in various applications of wireless network. A system of UAVs has the function of collecting data, offloading traffic for ground Base Stations (BSs) and illuminating coverage holes. However, inter-UAV interference is easily introduced because of the huge number of LoS paths in the air-to-ground channel. In this paper, we propose an interference management framework for UAV-assisted networks, consisting of two main modules: power control and UAV clustering. The power control is executed first to adjust the power levels of UAVs. We model the problem of power control for UAV networks as a non-cooperative game which is proved to be an exact potential game and the Nash equilibrium is reached. Next, to further improve system user rate, coordinated multi-point (CoMP) technique is implemented. The cooperative UAV sets are established to serve users and thus transforming the interfering links into useful links. Affinity propagation is applied to build clusters of UAVs based on the interference strength. Simulation results show that the proposed algorithm integrating power control with CoMP can effectively reduce the interference and improve system sum-rate, compared to Non-CoMP scenario. The law of cluster formation is also obtained where the average cluster size and the number of clusters are affected by inter-UAV distance.
Highlights
Unmanned Aerial Vehicle (UAV) has increasingly become a research hotspot due to its advantages of flexible deployment and low-cost [1]
We focus on the downlink transmission scenario, where UAVs form clusters to serve a group of users through cooperative transmission
The interference issue is much improved after previous power control stage; edge users located at the brink of the UAV coverage still have a high possibility to suffer severe interference from near-distant neighbor
Summary
UAV has increasingly become a research hotspot due to its advantages of flexible deployment and low-cost [1]. Integrating CoMP technology into UAV networks can avoid the strong interference caused by the interfering LoS path, thereby effectively increasing the user transmission rate This motivates us to design a new CoMP-based architecture for UAV-assisted wireless network. The authors in [13] studied the joint optimization of 3D locations, user association and power control in a SWIPT system. In [25], the authors considered a single-UAV mmwave SWIPT scenario, where two clustering algorithms: K-means and K-medoids are used to perform NOMA to maximize the harvested power for ground users. We design a CoMP-based power optimization and clustering algorithm in UAV-assisted network. Our algorithm can effectively avoid strong interference and increase user rate by power control and clustering.
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