2019 IEEE International Solid- State Circuits Conference - (ISSCC) 2019
DOI: 10.1109/isscc.2019.8662421
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30.5 A 1.41pJ/b 56Gb/s PAM-4 Wireline Receiver Employing Enhanced Pattern Utilization CDR and Genetic Adaptation Algorithms in 7nm CMOS

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Cited by 15 publications
(7 citation statements)
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“…At higher data rates, ISI is more detrimental, requiring more sophisticated filters. Moreover, the optimization of equalizer coefficients is a non-trivial problem, often requiring an LMS or even a genetic search algorithm [1], [18]. These controllers are also becoming more complex, worsening the problem.…”
Section: B Equalizationmentioning
confidence: 99%
“…At higher data rates, ISI is more detrimental, requiring more sophisticated filters. Moreover, the optimization of equalizer coefficients is a non-trivial problem, often requiring an LMS or even a genetic search algorithm [1], [18]. These controllers are also becoming more complex, worsening the problem.…”
Section: B Equalizationmentioning
confidence: 99%
“…A prototype of the proposed side-channel link is tested on a 7-nm FinFET 56 Gb/s PAM-4 transceiver from [2]. Fig.…”
Section: Measurement Resultsmentioning
confidence: 99%
“…In high-speed wireline communication links, limited channel bandwidth requires equalization in the transmitter (TX) and receiver (RX) to compensate for frequency-dependent loss [1]. Typically, the RX would employ adaptation algorithms to optimize their highly programmable equalizers to minimize bit error rate (BER) and power during operation [2], [3]. Highly programmable TXs are also available; however, without channel information, they can only be initialized to nominal settings at start-up, and cannot be dynamically adapted during operation [4].…”
Section: Introductionmentioning
confidence: 99%
“…QA amplifier (N=32) quantization levels before and after the GA optimization for sinusoidal input when the SNDR is noise-limited ral selection. GAs have been applied in analog design for automated circuit synthesis [24], [25] and finding optimal circuit coefficients for wireline receiver analog front-ends [26]. Moreover, GAs have the advantage of not having to rely on assumptions about the performance landscape, which in this case varies considerably based on the operative scenario, especially for wireless applications.…”
Section: A the Genetic Algorithmmentioning
confidence: 99%