多天线无人机辅助通信系统资源优化方案研究

Research on resource optimization scheme of multi-antenna UAV auxiliary communication system

为了提高传输的灵活性和有效性,提出了一种基于无人机(unmanned aerial vehicle,UAV)辅助通信系统资源优化方案。考虑无人机总能耗和飞行速度约束与用户的最低传输速率约束,构建了多用户总吞吐量最大化的资源分配问题。为了解决该非凸问题,采用块坐标下降法(block coordinate descent method,BCD)将此问题分解成2个非凸子问题,引入松弛变量、一阶泰勒表达式、连续凸近似(successive convex approximation,SCA)等方法分别将2个非凸子问题转换成凸问题求解,通过交替迭代优化,得出原非凸问题的近似次优解。仿真结果表明,所提算法的吞吐量比单一优化波束成形和单一优化UAV飞行速度分别提高了8.13 bit/s/Hz、6.32 bit/s/Hz,所提算法提高了系统的总吞吐量,并且具有良好的收敛性。

To improve the flexibility and effectiveness of transmission,a resource optimization scheme based on unmanned aerial vehicle(UAV)auxiliary communication system is proposed.Considering the total energy consumption and flight speed constraints of UAV and the minimum transmission rate constraints of users,a resource allocation problem is constructed to maximize the total throughput of multiple users.In order to solve the nonconvex problem,the block coordinate descent method(BCD)is used to decompose the problem into two nonconvex subproblems.The two non-convex subproblems are converted into convex problems by introducing slack variables,first-order Taylor expressions,and successive convex approximation(SCA),respectively.Through alternating iterative optimization,the approximate suboptimal solution of the original nonconvex problem is obtained.Simulation results show that the throughput of the proposed algorithm is 8.13 bit/s/Hz and 6.32 bit/s/Hz higher than that of single optimized beamforming and single optimized UAV,respectively.Therefore,the proposed algorithm improves the total throughput of the system and has good convergence.