Where Analog Meets Digital: Analog?to?Information Conversion and Beyond

Abstract

Energy efficiency, long battery life and low latency are some of the key attributes of many emerging ultralow power sensing and monitoring systems. Applications such as always-on reactive sensor systems for natural human-device interfaces and IoT for consumer and industrial applications require ultra-low power designs beyond the promises of state of the art data converters.These devices demand for a new approach to analog-digital system partitioning with the goal of significant overall reduction in energy consumption. Many IoT applications, unlike most multimedia systems, require signal information extraction or signature extraction, rather than full reconstruction of the original sensed waveforms. Under these conditions, Nyquist rate sampling may no longer offer the optimal digitization scheme. Recent work on alternative sensor digitization strategies target drastic sampling rate reduction in the ADC, while preserving the valuable relevant information (knowledge) present in the sensed signal. This paper aims to give an overview of this emerging field of analog-to-information conversion in light of various sub-Nyquist sampling techniques recently appearing in literature, as well as highlight new opportunities, challenges and applications emerging by such converters. I.Nyquist rate vs. Information rate: Over the last several decades, a growing number of signal processing architects have embraced intensive digital signal processing preceded by a standard analog frontend and analog-to-digital converter. This trend has been exacerbated by the exponential rate of miniaturization in silicon, growing complexity of signal processing algorithms, and more systematic digital design and technology porting compared to analog design in deep submicron technology nodes. The interface between analog and digital signals has as such generally been governed by sampling at or above the Nyquist sampling rate of the analog waveforms. The dimensionality of a bandlimited signal f(t) with a physical bandwidth W over a period of T is 2WT, indicating the number of samples sufficient for perfect digital signal reconstruction. Such sampling at the Nyquist rate of 2W ensures the integrity of the signal represented by samples which are Fourier series coefficients in a Fourier series expansion of function F(w) over fundamental interval [-W W] [1]. The original signal can subsequently be reconstructed by superimposing a set of orthogonal basis functions (sinc functions) weighted by the samples f(nT). Sampling the incoming signal at this rate hence guarantees that no information about the incoming signal is lost without taking into account any heuristic or a priori side information about the signal or its information content other than the physical bandwidth. While sampling at or above Nyquist rate offers a classic and straightforward approach, it can compromise overall power efficiency.

A 2.7μW/MIPS, 0.88GOPS/mm2 distributed processor for implantable brain machine interfaces

“…Similarly f s , V DD reflect the sampling frequency and supply voltage. Generally the scaling of R D constituents are well known and guide maximizing system efficiency in an abstract sense [10]. For the sake of this discussion we assert that analogue instrumentation is limited to a large extent to having an area power product R A larger than 10 −15 W m 2 when considering an SNR of 60 dB for a 1.2V system.…”

Analog-to-Information Converters: research trends and open problems

“…Applications such as always-on reactive sensors for natural human-device interfaces, as well as multiple consumer and industrial applications for the Internet of Things, require ultralow-power designs beyond the promise of state-of-the art data converters, memory chips and processing units [1].…”

Phase-Noise and Amplitude-Noise Measurement of DACs and DDSs

“…1-3], all the development is confidential. The technical information about converters and digital frequency synthesis is now in magazines [Mur15,Neu17,Cor04,Cor04,VB15,Win18] and books [Cla13], [HBM15], [Hoe16,Chap. 3], [Man12], [ML13,, [Sym13].…”