分布式认知雷达中的多人强盗
Multi-player Bandits for Distributed Cognitive Radar
摘要：
随着雷达网络的新应用，如汽车控制或室内定位，预计对频谱共享和通用互操作性的需求将会增加。本文介绍了应用程序的波形选择的多玩家强盗算法的分布式认知雷达网络，必须与通信系统共存。具体来说，我们假设网络中的雷达节点没有专用的通信信道。正如我们稍后将讨论的那样，节点可以通过采取故意干扰其他节点的行为并观察由此产生的冲突来间接通信。雷达节点试图优化它们自己的频谱利用率，同时避免冲突，不仅彼此冲突，而且与通信系统冲突。假设通信系统静态地占用雷达网络可用的频带的某个子集。首先，我们研究模型，假设每个节点经历等效的信道条件，然后研究放松这一假设的模型。
英文摘要：
With new applications for radar networks such as automotive control or indoor localization, the need for spectrum sharing and general interoperability is expected to rise. This paper describes the application of multi-player bandit algorithms for waveform selection to a distributed cognitive radar network that must coexist with a communications system. Specifically, we make the assumption that radar nodes in the network have no dedicated communication channel. As we will discuss later, nodes can communicate indirectly by taking actions which intentionally interfere with other nodes and observing the resulting collisions. The radar nodes attempt to optimize their own spectrum utilization while avoiding collisions, not only with each other, but with the communications system. The communications system is assumed to statically occupy some subset of the bands available to the radar network. First, we examine models that assume each node experiences equivalent channel conditions, and later examine a model that relaxes this assumption.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
