EAGER: SC2: A Universal Spectral Language for Blind Rendezvous in Open Spectrum Cognitive Intelligent Radio Networks

美国的无线基础设施通常被认为是该国经济繁荣和国家安全的关键。每条链路的数据速率在过去20年中呈指数级增长，如果无线电频谱拥堵的问题能够得到解决，预计这种增长将持续到未来。矛盾的是，在现代网络中，授权无线频谱拥堵的问题与整个频谱使用的稀缺性不一致--在任何给定的时刻只有10%的使用率。下一代无线的一种可能性是采用认知智能无线电，这种无线电可以在不中断现有系统的情况下“社交地”共享无线频谱，希望增加可用频谱的总体使用率。这些智能无线电将在频谱“交通”中穿行，就像人们可以想象的那样，自动驾驶汽车在不久的将来会这样；然而，与车辆不同的是，这些智能无线电中的两个必须在频谱的某个地方相遇，才能形成链接。这项工作提出了一种通用的频谱语言来实现认知智能无线电的会合。该项目的目标是创建一种语言，在这种语言中，任何可以感知或“查看”频谱的无线设备也可以通过频谱进行通信。这种方法是一种被动且非侵入性的方法，可通过设备到设备通信优化频谱使用。通用语言允许不同的设备组成网络，不匹配的网络在没有集中控制的情况下共享频谱。这种智能认知导致了用户和网络之间的冲突，影响了类似于人类行为的高效和公平的频谱接入。然后，自治网络的行为可以模仿这种社交行为，从而产生一种可能的频谱共享解决方案。该项目开发的算法将培育一种新的无线环境，模拟稳定的社会行为，使用认知智能无线电和通用通信，可以自然地产生智能和社交解决方案，以实现网络频谱共享。

The wireless infrastructure of the United States is often considered key to the country's economic prosperity and national security. The data rate per link has increased exponentially over the last 20 years and is expected to continue to do so into the future if the problem of congested radio frequency spectrum can be solved. Paradoxically, the issue of congested licensed wireless spectrum, in modern networks, is at odds with the sparsity of the entire spectrum usage - as little as 10% use at any given moment. One possibility for next-generation wireless is to employ cognitive intelligent radios that can "socially" share the wireless spectrum without disruption of preexisting systems in hopes of increasing the overall usage of available spectrum. These intelligent radios will weave through spectral "traffic" as one might envision autonomous vehicles doing someday in the near future; however, unlike vehicles, two of these intelligent radios must meet somewhere in spectrum in order to form a link. This work proposes a universal spectral language to enable rendezvous of cognitive intelligent radios.The objective of this project will be to create such a language where any wireless device that can sense or "look" at spectrum can also communicate via spectrum. This approach is a passive and noninvasive method for spectrum usage optimization with device-to-device communication. The universal language lets heterogeneous devices form networks and mismatched networks share the spectrum without centralized control. This intelligent cognition causes conflict among users and networks which affects efficient and fair spectrum access similar to the human behavior. The behavior of autonomous networks can then mimic this social behavior, leading to a possible solution to sharing spectrum. The algorithms developed on this project will foster a new wireless environment that mimics stable social behavior, using cognitive intelligent radios and universal communication that can lead naturally to intelligent and social solutions to network spectrum sharing.