Machine Learning

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A 65-nm CMOS Machine-Learning-Enhanced Bandwidth-Efficient LiDAR

A 65-nm CMOS Machine-Learning-Enhanced Bandwidth-Efficient LiDAR 150 150
Author(s): Pooya Poolad, Foad Arvani, Bahaa Radi, Ping-Hsuan Hsieh, Tony Chan Carusone

Abstract:

We present a proof-of-concept light detection and ranging (LiDAR) signal processing architecture that integrates a machine-learning-enhanced processing unit (PU) with on-chip time-to-digital converters (TDCs) to reduce bandwidth and memory requirements in SPAD-based direct time-of-flight (dToF) systems. The proposed architecture fits a Gaussian mixture model (GMM) to photon arrival time distributions …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 11
Year of Publication: 2026
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2026.3652972
Publisher: IEEE

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A Machine Learning-Inspired PAM-4 Transceiver for Medium-Reach Wireline Links

A Machine Learning-Inspired PAM-4 Transceiver for Medium-Reach Wireline Links 150 150
Author(s): Ramin Javadi, Tejasvi Anand

Abstract:

This article presents an energy-efficient machine learning-inspired PAM-4 wireline transceiver that leverages data encoding at the transmitter (Tx) and feature extraction with classification at the receiver (Rx) to compensate for channel loss ranging from 13 to 26 dB, while maintaining the bit error rate (BER)<10-11. A new consecutive symbol-to-center (CSC) encoding …

Published in: IEEE Journal of Solid-State Circuits
Page(s): 1 – 13
Year of Publication: 2025
Electronic ISSN: 1558-173X
DOI: 10.1109/JSSC.2025.3616072
Publisher: IEEE

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