无人机通感一体化系统轨迹优化及资源分配研究

    Joint Optimization of Trajectory and Resources allocation for UAV-Enable Integrated Sensing and Communication

    • 摘要: 在用户非均匀分布的情况下,进行基于非正交多址的无人机通信感知一体化系统设计,研究了将多个随机分布用户进行分簇后,对无人机进行轨迹设计、波束成形和功率分配,并建立联合优化问题,在考虑雷达回波保证感知性能的前提下的,以达到最大化最小用户速率的目的。由于建立的优化问题中存在多变量的耦合,属于一个非凸问题,为解决该非凸的优化问题,根据分簇后用户情况确定无人机的飞行轨迹后,原问题通过块坐标下降法分解成两个子问题,随后引入松弛变量化解变量耦合,结合连续凸近似和一阶泰勒表达式等数学方法,变换与求解子问题;最终通过对子问题交替迭代优化,得到原问题的近似最优解。经仿真结果验证,所提算法能有效提升系统平均吞吐量,且具备良好收敛性。

       

      Abstract: Abstract:  In the case of non-uniform user distribution, a unmanned aerial vehicle integrated sensing and communication system design based on non-orthogonal multiple access (NOMA) is conducted. After clustering multiple randomly distributed users, the research focuses on drone trajectory design, beamforming, and power allocation, and establishes a joint optimization problem. The objective is to maximize the minimum user rate under the premise of ensuring sensing performance via radar echoes. Due to the coupling of multiple variables in the established optimization problem, which belongs to a non-convex problem, after determining the drone's flight trajectory according to the clustered user conditions, the block coordinate descent method is employed to decompose the original problem into two subproblems. Then, by introducing slack variables, using first-order Taylor expansions, and applying successive convex approximation, the subproblems are transformed and solved. Finally, the approximate optimal solution to the original problem is obtained through alternating iterative optimization of the subproblems. Simulation results demonstrate that the proposed algorithm exhibits good convergence and can effectively improve the system's average throughput.

       

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