多无人机辅助NOMA网络的联合无线资源分配算法

Joint Wireless Resource Allocation Algorithm for Multi-UAV Assisted Downlink NOMA Networks

为了满足高容量需求和通信质量,提出了一种多无人机(Unmanned Aerial Vehicle, UAV)辅助下行非正交多址(Non-Orthogonal Multiple Access, NOMA)网络的联合定位、用户调度、用户配对和功率分配优化算法。在基站位置固定的网络场景下,推导出通用最优用户配对和功率分配策略闭式解。针对多小区场景,将无人机的位置优化问题转化为一个局部合作博弈问题,并证明所提博弈是一个精确的潜在博弈,它至少有一个纯策略纳什均衡(Pure Strategy Nash Equilibrium, PNE),且最优的纳什均衡(Nash Equilibrium, NE)能够最大化网络和速率。设计了一种集中分布式学习算法寻找最优PNE。仿真结果表明,该算法优于现有方案,显著提高了网络效用。

To meet requirement for high capacity and communication quality,a joint location,user scheduling,user pairing and power allocation optimization algorithm is proposed for multi-Unmanned Aerial Vehicle(UAV)assisted downlink Non-Orthogonal Multiple Access(NOMA)networks.Firstly,a closed solution of power distribution strategy and general optimal user pairing is derived with fixed location of base station.Then,the UAV location optimization problem is formulated as a local cooperation game for multi-cell scenario.In addition,the proposed game is proved as an exact potential game,which has at least one Pure Strategy Nash Equilibrium(PNE)and the best Nash Equilibrium(NE)can maximize the total network sum-rate.Finally,a centralized-distributed iterative learning algorithm is designed to explore the optimal PNE.Simulation results show that the proposed algorithm outperforms the existing schemes and has better performance in terms of system sum-rate.