Joint Optimization of Resource Allocation and Deployment Location in Unmanned Aerial Vehicle-Assisted Communication
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摘要:
为提升基于正交频分多址接入模式无人机辅助无线通信系统的网络性能,首先,以提升用户的公平性为系统方案设计指标,将包括子信道分配、调制模式选择、功率分配等通信资源和无人机位置联合建模为一个混合整数非线性优化问题;进一步,利用迭代优化的方式解决变量耦合性及非凸性等问题,将最大-最小问题转换为两个子问题:子信道分配和调制方式选择联合优化、无人机位置和子信道功率联合优化;然后,通过适当变换将子信道分配和调制方式选择联合优化建模为0-1线性优化问题进行求解,而无人机位置和子信道功率联合优化建模为凸优化问题求解;最后,进行实验仿真验证. 研究结果表明,所提联合优化算法相比基本方案可有效提升网络用户的公平性.
Abstract:To enhance the performance of the unmanned aerial vehicle (UAV)-assisted communication network based on the orthogonal frequency division multiple access (OFDMA) mode, the rational network allocation and optimal allocation of communication resources were studied. Firstly, in order to maximize the fairness of the network, a mixed-integer nonlinear maximum-minimum optimization problem was modeled by combining the communication resources including sub-channel allocation, modulation mode selection, and power allocation with UAV position. Then, the iterative optimization method was used to solve the problems of variable coupling and non-convex, and the maximum-minimum problem was converted into two sub-problems: joint optimization of sub-channel allocation and modulation mode selection and joint optimization of UAV position and sub-channel power. Finally, by means of appropriate transformations, the two subproblems were modeled into 0–1 linear optimization problem and convex optimization problem for solution. The experimental simulation results show that the proposed algorithm can jointly optimize multidimensional system parameters such as network allocation and communication resources, effectively enhance the fairness of network users, and improve network performance compared with other benchmark schemes.
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表 1 部分关键系统仿真参数
Table 1. Some key system simulation parameters
参数 数值 $ M $/个 20 $ H $/m 100 $ N $/个 100 $ B $/MHz 10 $ {\beta _0} $/dB −50 $ \delta _0^2 $/(dBm·Hz−1) −169 $ P_{\max }^{\mathrm{e}} $ $ {10^{ - 4}} $ $ {P_{\mathrm{T}}} $/dBm 22 -
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