Unmanned aerial vehicle- (UAV-) assisted communication has great potential to provide on-demand wireless services and improve the outdoor link throughput. In this paper, a UAV-based cognitive radio network (CRN) is investigated in which the UAV works as a secondary user (SU). Considering the overlay spectrum sensing mode, the UAV can operate on the licensed spectrum bands of primary user (PU) only when PU is idle. In each working frame structure, both sensing time slot and transmission time slot are analysed in radians. Specifically, our objective is to maximize the spectrum efficiency (SE) of the UAV by jointly optimizing the sensing radian and the number of radians. For the single-radian and multiradian schemes, the dichotomy and alternative iterative optimization (AIO) algorithm are proposed to solve the SE optimization problem. Simulation results show that the proposed multiradian cooperative spectrum sensing (CSS) scheme can achieve better performance on ensuring the quality-of-service (QoS) of the PU, and it can significantly enhance the SE of the UAV especially in the severe channel environments.

中文翻译：

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基于无人机的认知无线电网络的频谱效率优化

无人机（UAV）辅助通信在提供按需无线服务和提高室外链路吞吐量方面具有巨大潜力。在本文中，研究了一种基于UAV的认知无线电网络（CRN），其中UAV作为辅助用户（SU）工作。考虑到重叠频谱感测模式，只有当PU空闲时，UAV才能在主要用户（PU）的许可频谱带上运行。在每个工作帧结构中，都以弧度分析检测时隙和传输时隙。具体来说，我们的目标是通过共同优化感测弧度和弧度数量来最大化无人机的频谱效率（SE）。针对单弧度和多弧度方案，提出了二分法和替代迭代优化（AIO）算法来解决SE优化问题。