Wideband cognitive sensing from a few bits

来自几个比特的宽带认知感知

• 批准号: 1231504
• 负责人: Nikolaos Sidiropoulos
• 金额: $ 36万
• 依托单位: University of Minnesota-Twin Cities
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-10-01 至 2016-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1231504&HistoricalAwards=false
• 关键词: Wideband; cognitive; sensing; few; bits

Objective: Spectrum sensing is the most important element of cognitive radio, as it forms the ba-sis for adaptive spectrum sharing. Wideband spectrum sensing without frequency sweeping orNyquist-rate sampling is a challenging problem, especially for network sensing from low-end sen-sors with limited communication capabilities. Assume that each sensor can only down-convert,filter, and send out a binary signal when it measures energy above threshold at its filter?s output.Is it possible to form a satisfactory estimate of the ambient power spectrum using just a few suchbits? This is the question at the core of this project, and exciting preliminary results suggest thatthe answer is on the affirmative. A well-rounded research program has been designed to buildupon these preliminary findings. The research will evolve along four thrusts: i) core system designand performance analysis; ii) distributed implementation; iii) relevant extensions, such as adaptivesensing; and iv) software radio experiments.Intellectual merit: Power spectrum estimation from few wideband energy detection bits has neverbeen considered - yet is a fundamental extension of spectral analysis. Exciting new applicationsof convex optimization theory and methods will be found in the area of network-based spectrumestimation.Broader impacts: Wideband spectrum sensing using cheap sensors and few bits is a transformativeidea that has the potential to permeate the benefits of cognitive radio down to commodity hardware- something currently far from reality. The topic is highly conducive for involving students andtraining the next generation of wireless engineers.

目的：频谱感知是认知无线电的重要组成部分，是实现自适应频谱共享的基础。没有扫频和奈奎斯特采样的宽带频谱感知是一个具有挑战性的问题，特别是对于通信能力有限的低端传感器的网络感知。假设每个传感器只能在其滤波器S输出的能量超过阈值时对其进行下变频、滤波和发出二进制信号。仅用几个这样的比特就能形成令人满意的环境功率谱估计吗？这是这个项目的核心问题，令人兴奋的初步结果表明，答案是肯定的。在这些初步发现的基础上，设计了一个全面的研究计划。这项研究将沿着四个方向发展：i)核心系统设计和性能分析；ii)分布式实现；iii)相关扩展，如自适应感知；以及iv)软件无线电实验。智力优势：从未考虑过从少数宽带能量检测比特进行功率谱估计-但却是频谱分析的基本扩展。凸优化理论和方法将在基于网络的频谱估计领域找到令人兴奋的新应用。广泛的影响：使用廉价传感器和少量比特的宽带频谱感知是一种变革性的想法，有可能将认知无线电的好处渗透到商用硬件--目前还远未实现。本课题对吸引学生参与，培养下一代无线工程师大有裨益。