论文标题
自适应和公平部署方法以平衡多uav蜂窝网络中的卸载流量
Adaptive and Fair Deployment Approach to Balance Offload Traffic in Multi-UAV Cellular Networks
论文作者
论文摘要
无人驾驶飞机辅助通信（UAB-BS）是一种有前途的解决方案，可以在突然/临时拥挤的事件中建立无线连通性，因为它比传统的地面基站（GBS）更灵活和移动性。由于这些好处，无人机可以轻松地在高海拔地区部署，以提供比GBS更多的视线（LOS）链接。因此，地面上的用户可以获得更可靠的无线通道。实际上，地面用户的移动性质可以在不同的时间和空间中创建不均匀的用户密度。这种现象会导致UAV-BSS之间的用户关联不平衡，并可能导致无人机BBS过载。我们提出了一种三维自适应和公平的部署方法来解决这个问题。所提出的方法可以共同优化UAV-B的高度和传输功率，以从超载的UAV-BSS中卸载流量。仿真结果表明，与直接贪婪的方法相比，总能效率的网络性能在总容量中提高了37.71％，总能源效率为37.48％，Ja那教公平指数提高了16.12％。
Unmanned aerial vehicle-aided communication (UAB-BS) is a promising solution to establish rapid wireless connectivity in sudden/temporary crowded events because of its more flexibility and mobility features than conventional ground base station (GBS). Because of these benefits, UAV-BSs can easily be deployed at high altitudes to provide more line of sight (LoS) links than GBS. Therefore, users on the ground can obtain more reliable wireless channels. In practice, the mobile nature of the ground user can create uneven user density at different times and spaces. This phenomenon leads to unbalanced user associations among UAV-BSs and may cause frequent UAV-BS overload. We propose a three-dimensional adaptive and fair deployment approach to solve this problem. The proposed approach can jointly optimize the altitude and transmission power of UAV-BS to offload the traffic from overloaded UAV-BSs. The simulation results show that the network performance improves by 37.71% in total capacity, 37.48% in total energy efficiency and 16.12% in the Jain fairness index compared to the straightforward greedy approach.
