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Record W3120447091 · doi:10.1109/ojcas.2020.3040947

A Study of Discrete Multitone Modulation for Wireline Links Beyond 100 Gb/s

2021· article· en· W3120447091 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Open Journal of Circuits and Systems · 2021
Typearticle
Languageen
FieldEngineering
TopicAdvanced Wireless Communication Techniques
Canadian institutionsHuawei Technologies (Canada)University of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsWirelineBit error rateModulation (music)Digital subscriber lineComputer scienceElectronic engineeringChannel (broadcasting)JitterBasebandEqualization (audio)Pulse-amplitude modulationTopology (electrical circuits)Electrical engineeringTelecommunicationsPhysicsWirelessEngineeringPulse (music)Bandwidth (computing)

Abstract

fetched live from OpenAlex

To overcome the severe losses beyond 28 GHz in low-cost electrical channels, 4-level pulse-amplitude modulation (4-PAM) wireline links targeting 112 Gb/s incorporate resourceor power-intensive equalization schemes such as decision-feedback equalizers (DFE) with many taps. Alleviating the timing constraints that cause DFEs to balloon in size and power, discrete multitone (DMT) modulation involves independent sub-channels that can be equalized in the frequency domain without feedback. DMT allows flexibility in assigning bits to each sub-channel, thereby potentially avoiding lossy parts of the frequency spectrum. This article presents behavioural modeling results and an experimental setup used to study DMT transceivers. Our simulations show 200 Gb/s operation at a bit error rate (BER) of less than 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-5</sup> over an IEEE P802.3ck channel with 21 dB of loss at 50 GHz and assuming 150 fsrms of jitter, 1.26 mVrms of noise at the receiver's input, and 7-bit 80 GS/s data converters. An updated bit-loading algorithm led to BER values 1-2 orders of magnitude below our previous results. The estimated power and area of the associated digital signal processing are comparable to those of DFE. We also present an experimental DMT setup achieving 61.6 Gb/s at a BER of 8.6 × 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-4</sup> over a physical channel with severe notches that is very challenging for 4-PAM.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.242
Threshold uncertainty score0.364

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.052
GPT teacher head0.327
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it