Physical Reservoir Signal Acquisition for Sub-Nyquist Waveform Reconstruction
For signal acquisition and compressed sensing, RSA offers a new hardware-based approach to sub-Nyquist sampling, potentially reducing ADC requirements in high-bandwidth applications.
This paper introduces reservoir signal acquisition (RSA), a new paradigm where a physical reservoir is used as a dynamical measurement device to reconstruct broadband waveforms from sub-Nyquist samples. The method achieves exact reconstruction when the number of measurement channels meets the undersampling ratio, and experimentally reconstructs 12.5 GHz signals using ADCs with four times lower Nyquist frequency.
Physical reservoir computing has traditionally exploited the dynamics of physical systems for computation, enabling tasks such as inference, classification, and prediction. Here, we introduce a fundamentally different paradigm for exploiting physical reservoirs, termed "reservoir signal acquisition" (RSA), in which a physical reservoir serves as a dynamical measurement device rather than a computational engine. In RSA, the reservoir transforms an unknown broadband waveform into a diverse set of measurements, enabling waveform reconstruction from low-rate samples beyond the Nyquist limit of any individual acquisition channel. We show that exact reconstruction of arbitrary broadband signals is achieved when the number of measurement channels satisfies $M \geq N_R$, where $N_R$ is the undersampling ratio. Moreover, spectrally or temporally sparse signals can be recovered even when $M \ll N_R$, demonstrating a compressed-sensing capability that naturally emerges from the diversity of reservoir dynamics. We experimentally validate RSA using a silicon photonic reservoir circuit. With a data-driven calibration requiring no physical model of the device, we reconstruct radio-frequency signals up to 12.5 GHz using only low-rate analog-to-digital converters (ADCs), corresponding to four times the Nyquist frequency of each ADC. These results establish RSA as a new signal acquisition paradigm based on physical reservoirs, extending their role from computation to sub-Nyquist acquisition of broadband waveforms.