基于无人机通信的蜂窝网流量卸载研究

UAV assisted traffic offloading in cellular networks

在传统的地面蜂窝网络中,位于小区边缘的移动终端与服务地面基站的距离较远,因此在地面基站负载较重的热点期间常常会造成性能瓶颈。无人机具有高灵活性和高移动性,可作为移动基站为地面基站减轻数据流量负载,提高用户的服务质量,同时降低电信运营商用于基础设施建设的投资成本。因此文中提出UAV(Unmanned Aerial Vehicle)为多小区的边缘用户提供服务以减轻基站的流量负载。为保障用户的服务质量,在满足所有用户速率的前提下,联合优化用户卸载时长调度和UAV轨迹,最大化边缘用户的吞吐量。目标问题是一个非凸的问题,利用一般方法难以解决,因此文中提出了一个两阶段的替代算法(TSI),将目标问题分解为两个子问题,利用SCA(Successive Convex Approximation)方法将非凸问题转化为凸问题,通过交替优化无人机轨迹和边缘用户卸载时长调度来解决目标问题。仿真结果表明了提出的方法具有有效性。

In conventional terrestrial cellular networks,mobile terminals at the cell edge often pose a performance bottleneck due to their long distance from the ground base stations,especially in a hotspot period when the ground base station is heavily loaded.Unmanned aerial vehicles(UAVs)with high flexibility and high mobility,as mobile base stations,can reduce traffic load for ground base stations,thus improving user service quality,and reducing the investment cost of telecommunication operators for infrastructure construction at the same time.Thus,this paper proposes that UAV can provide services for edge users in multiple cells to reduce the traffic of the base station.In the proposed scheme,the sum throughput of UAV-served users is maximized subject to the rate requirements of all users by optimizing the UAV trajectory and offloading duration each flying circle.The optimization is a nonconvex problem that is difficult to solve.A two-stage iterative algorithm TSI is proposed for solving the formulated problem,which divides the optimization into two sub-problems.Non-convex problem is transformed into a convex problem by using the SCA(Success Convex Approximation)method,and the target problem is solving by optimizating the trajectory and user offloading duration schedule alternately.Simulation results shows the effectiveness of the proposed scheme.