Abstract

This paper presents an event-driven Discrete-Time Level Crossing Analog-to-Digital Converter (DT-LCADC) that is energy-efficient in the conversion of both sparse and generic signals, and exploits signal sparsity to reduce the output data rate. The proposed DT-LCADC uses the comparator delay, to classify each level-crossing event as slow or fast, according to the rate of change of the input signal. The converter can adaptively select the most suitable search scheme, between linear and binary, according to the type of event. The proposed DTLCADC, manufactured with 65 nm CMOS technology, achieves 9.98 ENOB and a signal bandwidth of 8 kHz, while consuming between 100 and 260 nW from a 0.8 V supply, depending on the input signal. The corresponding Walden FoMW ranges from 6.2 to 16.1 fJ/c.s, achieving a more than 4 X improvement in worstcase power efficiency compared to state-of-the-art DT-LCADCs. To convert time-sparse neural signals, the proposed ADC requires only 110 nW, while reducing the output data rate down to 8.9 kb/s. This leads to a compression ratio of 94.4%, compared to a Nyquist ADC with the same accuracy.

Original languageEnglish
Title of host publication2025 IEEE European Solid-State Electronics Research Conference, ESSERC 2025
PublisherInstitute of Electrical and Electronics Engineers
Pages557-560
Number of pages4
ISBN (Electronic)979-8-3315-2539-2
DOIs
Publication statusPublished - 5 Nov 2025
Event51st IEEE European Solid-State Electronics Research Conference, ESSERC 2025 - Munich, Germany
Duration: 8 Sept 202511 Sept 2025

Conference

Conference51st IEEE European Solid-State Electronics Research Conference, ESSERC 2025
Country/TerritoryGermany
CityMunich
Period8/09/2511/09/25

Bibliographical note

Publisher Copyright:
© 2025 IEEE.

Keywords

  • Data Compression
  • Edge Computing
  • Event-Based Sensor Interface
  • Level-Crossing ADC
  • Time-sparse signal

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