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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。
Abstract：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.
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基本信息:
中图分类号:TN929.5;V279
引用信息:
[1]邵鸿翔,孙有铭,冀保峰,等.多无人机辅助NOMA网络的联合无线资源分配算法[J].无线电工程,2024,54(03):565-572.
基金信息:
国家自然科学基金(61901518); 河南省科技厅科技攻关项目(222102210094,232102210065)~~