Rate Splitting Multiple Access for Joint Communication and Sensing Systems with Unmanned Aerial Vehicles

Yuwei Li, Wanli Ni, Hui Tian, Meihui Hua, Shaoshuai Fan
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引用次数: 4

Abstract

This paper investigates the problem of resource allocation for joint communication and radar sensing system on rate-splitting multiple access (RSMA) based unmanned aerial vehicle (UAV) system. UAV simultaneously communicates with multiple users and probes signals to targets of interest to exploit cooperative sensing ability and achieve substantial gains in size, cost and power consumption. By virtue of using linearly precoded rate splitting at the transmitter and successive interference cancellation at the receivers, RSMA is introduced as a promising paradigm to manage interference as well as enhance spectrum and energy efficiency. To maximize the energy efficiency of UAV networks, the deployment location and the beamforming matrix are jointly optimized under the constraints of power budget, transmission rate and approximation error. To solve the formulated non-convex problem efficiently, we decompose it into the UAV deployment subproblem and the beamforming optimization subproblem. Then, we invoke the successive convex approximation and difference-of-convex programming as well as Dinkelbach methods to transform the intractable subproblems into convex ones at each iteration. Next, an alternating algorithm is designed to solve the non-linear and non-convex problem in an efficient manner, while the corresponding complexity is analyzed as well. Finally, simulation results reveal that proposed algorithm with RSMA is superior to orthogonal multiple access and power-domain non-orthogonal multiple access in terms of power consumption and energy efficiency.
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无人机联合通信与传感系统的分频多址
研究了基于速率分裂多址(RSMA)的无人机系统中联合通信和雷达传感系统的资源分配问题。无人机同时与多个用户通信,探测信号到感兴趣的目标,利用协同传感能力,在尺寸、成本和功耗方面取得实质性的收益。由于在发送端使用线性预编码速率分裂,在接收端使用连续干扰消除,RSMA被引入作为一种有前途的范例来管理干扰以及提高频谱和能源效率。为了使无人机网络的能源效率最大化,在功率预算、传输速率和近似误差约束下,对部署位置和波束形成矩阵进行了联合优化。为了有效地求解公式化的非凸问题,我们将其分解为无人机部署子问题和波束成形优化子问题。然后,我们利用连续凸逼近和凸差分规划以及Dinkelbach方法在每次迭代中将棘手的子问题转化为凸问题。其次,设计了一种交替算法,以有效地求解非线性非凸问题,并分析了相应的复杂性。仿真结果表明,该算法在功耗和能效方面均优于正交多址和功率域非正交多址。
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