Interference Management in UAV-Assisted Multi-Cell Networks - Muchen Jiang; Honglin Ren; Yongxing Qi; Ting Wu (Information)
This article considers a multi-cell wireless network comprising of conventional user equipment (UE), sensor devices and unmanned aerial vehicles (UAVs) or drones. UAVs are used to assist a base station, e.g., improve coverage or collect data from sensor devices. The problem at hand is to optimize the (i) sub-carrier assigned to a cell or base station, (ii) position of each UAV, and (iii) transmit power of the following nodes: base stations and UAVs. We outline a two-stage approach to maximize the fairness-aware sum-rate of UE and UAVs. In the first stage, a genetic algorithm (GA)-based approach is used to assign a sub-band to all cells and to determine the location of each UAV. Then, in the second stage, a linear program is used to determine the transmit power of UE and UAVs. The results demonstrate that our proposed two-stage approach achieves approximately 97.43% of the optimal fairness-aware sum-rate obtained via brute-force search. It also attains on average 98.78% of the performance of a computationally intensive benchmark that requires over 478% longer run-time. Furthermore, it outperforms a conventional GA-based sub-band allocation heuristic by 221.39%.