NOMA-based joint optimization of trajectory and resources for UAV-enable integrated sensing and communication system
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摘要:
针对当前无线频谱资源紧张和多用户信号间的干扰，探讨了在非正交多址接入(NOMA)技术支持下，无人机通信感知一体化(ISAC)系统中的感知目标选择、波束成形及无人机飞行轨迹和速度的联合优化问题，旨在提高系统的吞吐量。针对该问题的非凸特性，采用块坐标下降(BCD)法，将复杂问题拆分为3个子问题。求解子问题时，引入松弛变量、一阶泰勒近似和连续凸近似(SCA)技术，简化计算过程，并提高求解效率。通过交替迭代以上子问题，得到原问题的近似最优解。仿真验证了所提算法的有效性，可有效提高系统最大平均吞吐量，并展示了良好的收敛性。
Abstract:This study examines the difficulties of target selection, beamforming, and the combined optimization of UAV trajectory and speed inside the integrated sensing and communication (ISAC) architecture in order to address the shortage of wireless spectrum resources and the interference among multi-user signals. By leveraging non-orthogonal multiple access (NOMA) technology, the overall system throughput is enhanced. Given the non-convex nature of the problem, this research employs the block coordinate descent (BCD) method to decompose the intricate problem into three manageable subproblems. Utilizing relaxation variables, first-order Taylor approximation, and successive convex approximation (SCA), the method reduces computational complexity and improves efficiency. Alternating iterations of these subproblems yield an approximately optimal solution to the original problem. The suggested algorithm's effectiveness is confirmed by simulation results, which show how it may greatly increase maximum average throughput and exhibit strong convergence.
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图 3 不同方案下迭代次数与最大平均吞吐量的关系
Figure 3. Relationship between number of iterations and maximum average throughput under different schemes
图 4 不同方案下最大发射功率与最大平均吞吐量关系
Figure 4. Relationship between maximum transmit power and maximum average throughput under different schemes
图 5 不同飞行周期下能耗的关系
Figure 5. Relationship of energy consumption under different flight cycles
图 7 不同方案下有效感知功率与最大平均吞吐量的关系
Figure 7. Relationship between effective sensing power and maximum average throughput under different schemes
图 8 不同用户数目和感知目标数下最大平均吞吐量与最大发射功率的关系
Figure 8. Relationship between maximum average throughput and maximum transmit power under different number of users and perceived target number
表 1 不同方案获得的发射波束图角度
Table 1. Angle of transmitting beam pattern obtained by different schemes
方案 UAV位置/m 期望角度/(°) 实际角度/(°) 最大增益 本文方案 [142,165,100] 43.02 43.37 251.06 方案1 [80,177,100] 37.60 10.30 122.13 方案2 [90,223,100] 51.17 52.30 125.53 方案3 [150,150,100] 41.93 59.35 132.05 
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