IHCS: Collaborative Research: Compressive Spectrum Sensing in Cognitive Radio Networks

IHCS：协作研究：认知无线电网络中的压缩频谱感知

• 批准号: 1028790
• 负责人: Yin Zhang
• 金额: $ 25万
• 依托单位: William Marsh Rice University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1028790&HistoricalAwards=false
• 关键词: IHCS; Collaborative; Research; Compressive; Spectrum

The objective of this research is to improve design of collaboratively discovering unused spectrum in a revolutionary wireless communication paradigm, the cognitive-radio network, in which cognitive-radio users can detect and share the unused spectrum. The proposed approach is to apply collaborative compressive sensing to increase spectrum sensing bandwidth, speed, and accuracy. Specifically, the cognitive radios, rather than sweeping a set of channels sequentially, will sense linear combinations of the powers of multiple channels and report them to the fusion center, where the occupied channels are recovered using compressive sensing algorithms. Missing and erroneous reports can be exactly recovered by matrix completion since the matrix of all reports has a low-rank. Prior knowledge of channel gains is not required. The system computes more but senses much less and faster, which will be validated by both numerical and USRP2-based simulations.The proposed research is potentially transformative as the novel framework and algorithms will broadly apply to signal sensing involving multiple sensors, modalities, and data sources. This research will have a broader impact on several audiences. The study of the jointly-sparse signal reconstruction will contribute to researchers working in compressive sensing and wireless networks. The hardware implementation will bring fresh ideas to the industrial community. The proposed research will be integrated into the existing combined education/research effort at the University of Houston and Rice University, improve education of under-represented minorities at the two institutions, and expose students to state-of-the-art research in wireless networks and compressive sensing through the NSF sponsored VIGRE program.

这项研究的目的是改善在革命性的无线通信范式（Cognitive-Radio Network）中进行协作发现未使用频谱的设计，认知 - 拉迪奥用户可以在该网络中检测并共享未使用的频谱。提出的方法是应用协作压缩感知以增加频谱感知带宽，速度和准确性。具体而言，认知无线电而不是依次扫描一组通道，将感觉到多个通道的力量的线性组合，并将其报告给融合中心，在该中心使用压缩感测算法恢复了占用的通道。由于所有报告的矩阵都有低级别，因此可以通过矩阵完成删除丢失和错误的报告。不需要对渠道提升的先验知识。该系统的计算更多，但感觉更少，更快，这将通过数值和基于USRP2的模拟验证。拟议的研究具有潜在的变化性，因为新型框架和算法将广泛地适用于涉及多种传感器，模式和数据源的信号传感。这项研究将对几个受众产生更大的影响。 联合信号重建的研究将有助于从事压缩传感和无线网络的研究人员。硬件实施将为工业社区带来新的想法。拟议的研究将纳入休斯敦大学和赖斯大学现有的联合教育/研究工作，改善对这两个机构的代表性不足的少数群体的教育，并通过NSF赞助的Vigre计划使学生了解无线网络的最先进研究，并通过NSF Sents进行最新的研究。