Robust Compressive Sensing: Circuits and Algorithms

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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.