The joint unmanned aerial vehicle(UAV) trajectory and power allocation optimization for Non-orthogonal multiplex access (NOMA) protocol in cognitive radio network is investigated in this paper. In the considered system, the UAV node transmits data streams to multiple secondary users by using NOMA protocol under the interference constraint to the primary user. In order to maximize the sum rate of all secondary users, the UAV trajectory as well as the total transmission power and the power allocation scheme for NOMA should be carefully designed. Firstly, the optimization problem is modeled and formulated with interference and flying velocity constraints. Considering the non-convexity of the joint optimization, the alternate optimization algorithm is proposed. During the iteration procedure, the power allocation scheme is firstly solved by successive convex optimization tools with given UAV trajectory and total transmission power. Afterwards, with the help of optimal power allocation scheme, the UAV trajectory as well as the total transmission power is iterative optimized by using of Taylor series approximation. Simulation results are provided to verify the convergence and the effectiveness of the proposed algorithm as well as the effects of system parameters.

研究了认知无线电网络中非正交多路访问（NOMA）协议的联合无人机轨迹和功率分配优化。在所考虑的系统中，UAV节点在对主用户的干扰约束下，通过使用NOMA协议将数据流传输到多个辅助用户。为了最大化所有次要用户的总和率，应仔细设计UAV轨迹以及总发射功率和NOMA的功率分配方案。首先，利用干扰和飞行速度约束对优化问题进行建模和公式化。考虑联合优化的非凸性，提出了一种替代优化算法。在迭代过程中，首先用给定的无人机轨迹和总发射功率的连续凸优化工具求解功率分配方案。然后，借助最优功率分配方案，利用泰勒级数逼近法对无人机轨迹以及总发射功率进行迭代优化。仿真结果提供了验证算法的收敛性和有效性以及系统参数的影响。