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基于智能反射面辅助与无线中继的无人机协作通信系统优化算法
引用本文:李一聪,黄高飞,周发升,赵赛,唐冬. 基于智能反射面辅助与无线中继的无人机协作通信系统优化算法[J]. 计算机应用研究, 2022, 39(7)
作者姓名:李一聪  黄高飞  周发升  赵赛  唐冬
作者单位:广州大学电子与通信工程学院,广州510006
基金项目:国家自然科学基金资助项目(61872098,61902084);广东省自然科学基金资助项目(2021A1515011812)
摘    要:针对采用智能反射面(RIS)辅助与解码转发中继的无人机协作通信系统,研究了RIS反射相位、无人机部署位置和无线中继传输时隙联合优化算法。首先根据协作系统传输协议,建立了以最大化系统端到端信息传输可达速率为目标的资源分配联合优化问题。该问题非凸,为此提出一个交替优化算法,将该非凸问题分解为分别对RIS反射相位、无人机部署位置和协作中继传输时隙进行优化的三个子问题。其中RIS反射相位优化子问题和无人机部署位置优化子问题仍非凸,为此,分别采用半定松弛方法和提出一种基于连续凸逼近的局部区域优化方法进行求解,通过三个子问题的交替和迭代优化得到原问题的次优解。仿真结果验证了提出的联合优化算法获得的系统端到端信息传输可达速率优于其他的基准方案,并发现无人机应部署靠近中继或RIS的上方,其结果与系统的信噪比、RIS的反射元件数量以及RIS和中继所处地理位置等因素有关。

关 键 词:智能反射面  解码转发中继  无源波束成形  时间分配  无人机通信
收稿时间:2021-12-14
修稿时间:2022-06-23

Joint optimization algorithm for reconfigurable intelligent surface and wireless relaying assisted UAV communication system
Li Yicong,Huang Gaofei,Zhou Fasheng,Zhao Sai and Tang Dong. Joint optimization algorithm for reconfigurable intelligent surface and wireless relaying assisted UAV communication system[J]. Application Research of Computers, 2022, 39(7)
Authors:Li Yicong  Huang Gaofei  Zhou Fasheng  Zhao Sai  Tang Dong
Affiliation:Guangzhou University,,,,
Abstract:For reconfigurable intelligent surface(RIS) and decode-and-forward(DF) relaying assisted unmanned aerial vehicle(UAV) communication system, this paper proposed a joint optimization algorithm to optimize the reflection phase of RIS, the deployment location of UAV, and time allocation for DF relay. First, it formulated a joint resource allocation optimization problem for maximizing achievable transmission rate. The problem was non-convex, thus it derived an alternating optimization algorithm that decomposed the non-convex problem into three sub-problems that optimized the reflection phase of RIS, the UAV deployment location, and the cooperative relay transmission time slot, respectively. Among them, the reflection phase optimization sub-problem and the UAV deployment location optimization sub-problem were still non-convex. Therefore, it used the semidefinite relaxation method and a local area optimization method based on successive convex approximation to solve the two problems, respectively. The research obtained the sub-optimal solution of the original problem by alternating and iterative optimization of the three sub-problems. The simulation results verify that the proposed joint optimization algorithm can obtain a higher system achievable transmission rate than other benchmark schemes, and the optimal deployment position of the UAV is close to above the relay or above the RIS, which is related to factors such as the signal-to-noise ratio of the system, the number of reflective elements of RIS, and the geographical locations of RIS and relay.
Keywords:reconfigurable intelligent surface(RIS)   decode-and-forward(DF) relay   passive beamforming   time allocation   unmanned aerial vehicle(UAV) aided communication
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