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Secrecy rate maximization for 6G cognitive satellite-UAV networks
China Communications Pub Date : 2023-02-07 , DOI: 10.23919/jcc.2023.01.020
Chengleyang Lei, Wei Feng, Yunfei Chen, Ning Ge

To cover remote areas where terrestrial cellular networks may not be available, non-terrestrial infrastructures such as satellites and unmanned aerial vehicles (UAVs) can be utilized in the upcoming sixth-generation (6G) era. Considering the spectrum scarcity problem, satellites and UAVs need to share the spectrum to save costs, leading to a cognitive satellite-UAV network. Due to the openness of both satellite links and UAV links, communication security has become a major concern in cognitive satellite-UAV networks. In this paper, we safeguard a cognitive satellite-UAV network from a physical layer security (PLS) perspective. Using only the slowly-varying large-scale channel state information (CSI), we jointly allocate the transmission power and subchannels to maximize the secrecy sum rate of UAV users. The optimization problem is a mixed integer nonlinear programming (MINLP) problem with coupling constraints. We propose a heuristic algorithm which relaxes the coupling constraints by the penalty method and obtains a sub-optimal low-complexity solution by utilizing random matrix theory, the max-min optimization tool, and the bipartite graph matching algorithm. The simulation results corroborate the superiority of our proposed scheme.

中文翻译:

6G 认知卫星-无人机网络的保密率最大化

为了覆盖可能无法使用地面蜂窝网络的偏远地区,可以在即将到来的第六代 (6G) 时代利用卫星和无人驾驶飞行器 (UAV) 等非地面基础设施。考虑到频谱稀缺问题,卫星和无人机需要共享频谱以节省成本,从而产生认知卫星-无人机组网。由于卫星链路和无人机链路的开放性,通信安全成为认知卫星-无人机网络的主要关注点。在本文中,我们从物理层安全 (PLS) 的角度保护认知卫星-无人机网络。仅使用缓慢变化的大规模信道状态信息 (CSI),我们联合分配传输功率和子信道,以最大化无人机用户的保密和率。优化问题是具有耦合约束的混合整数非线性规划 (MINLP) 问题。我们提出了一种启发式算法,利用随机矩阵理论、最大-最小优化工具和二分图匹配算法,通过惩罚方法放松耦合约束并获得次优低复杂度解。仿真结果证实了我们提出的方案的优越性。
更新日期:2023-02-10
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