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国家经济繁荣和国家安全的关键。在过去的20年里，每条链路的数据速率呈指数级增长，如果能够解决无线电频谱拥挤的问题，预计未来还会继续这样做。矛盾的是，在现代网络中，授权无线频谱拥挤的问题与整个频谱使用的稀疏性是不一致的——在任何给定时刻只有10%的使用。下一代无线技术的一种可能是采用认知智能无线电，这种无线电可以在不破坏现有系统的情况下“社会地”共享无线频谱，以期提高可用频谱的总体利用率。这些智能无线电将在频谱“交通”中编织，就像人们想象的在不久的将来某一天自动驾驶汽车所做的那样；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连接。这项工作提出了一种通用的频谱语言，以实现认知智能无线电的交会。这个项目的目标是创造这样一种语言，任何可以感知或“看到”频谱的无线设备也可以通过频谱进行通信。该方法是一种无源、无创的设备对设备通信频谱使用优化方法。通用语言允许异构设备组成网络，不匹配的网络共享频谱，而无需集中控制。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、公平的频谱接入。自主网络的行为可以模仿这种社会行为，从而导致共享频谱的可能解决方案。该项目开发的算法将培育一个新的无线环境，模仿稳定的社会行为，使用认知智能无线电和通用通信，可以自然地为网络频谱共享提供智能和社会解决方案。

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.