Robust Compressive Sensing: Circuits and Algorithms

目的：该计划的目的是共同设计压缩/低速率宽带接收机的电路和算法，这些接收机对传感和通信应用中遇到的大型干扰器产生的非理想性具有鲁棒性。因此，该计划提供了两个变革性的观点：（1）使用压缩感知方法解决宽带应用中的干扰问题，以及（2）拓宽压缩感知的理论基础，以包括具有弱非线性的系统。智力价值：智力价值围绕着联合收割机电路和匹配压缩感知方法的两个重点：（1）通过结合对电路的观察（设备对于小幅度是线性的）和压缩感知（随机子采样是频率稀疏信号的有效捕获方法），该项目正在设计非线性感知模拟-信息转换器，该转换器选择在测量过程中保持线性的样本;（2）通过结合关于通信环境的先验知识，（常见干扰的表征）与用于干扰消除的算法工具，该项目正在设计解调器序列和匹配的恢复算法，这些算法考虑到模拟-信息转换器的非线性，并使DSP-更广泛的影响：该项目的更广泛的影响包括能够更有效地使用非常宝贵的通信频谱的创新。 具体而言，它影响了宽带系统的关键干扰问题和压缩感知新兴领域的方向。它影响了许多应用，从新兴的认知无线电到环境传感系统。最后，该项目包括一个积极的教育参与的综合方案，从K-12到研究生院。

Objective:The objective of this program is to co-design circuits and algorithms for compressive/low rate wideband receivers that are robust to the non-idealities that arise with the large interferers that will be encountered in sensing and communication applications. The program thus provides two transformative perspectives: (1) solving the interference problem in wideband applications using compressive sensing approaches, and (2) broadening the theoretical basis for compressive sensing to include systems with weak nonlinearity.Intellectual merit:The intellectual merit is centered around two thrusts that combine circuit and matched compressive sensing approaches: (1) By combining observations on circuits (devices are linear for small amplitudes) and compressive sensing (randomized subsampling is an effective acquisition approach for frequency-sparse signals), the project is designing nonlinearity-aware analog-to-information converters that select samples that preserve linearity in the measurement process; (2) By combining prior knowledge on the communication environment (characterizations of common interferers) with algorithmic tools for interference cancellation, the project is designing demodulator sequences and matched recovery algorithms that account for the nonlinearity of the analog-to-information converter and enable DSP-based interference cancellation.Broader Impacts:The broader impacts of this project include innovations that enable much more efficient use of the very valuable communication spectrum. Specifically, it affects the critical interference problem for wideband systems and the direction of the emerging field of compressive sensing. It impacts numerous applications, ranging from emerging cognitive radios to environmental sensing systems. Finally, the project includes an integrated program of active educational engagement at levels ranging from K-12 to graduate school.