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Record W2098368256 · doi:10.1109/jlt.2013.2244847

Low Overhead Intra-Symbol Carrier Phase Recovery for Reduced-Guard-Interval CO-OFDM

2013· article· en· W2098368256 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.

Bibliographic record

VenueJournal of Lightwave Technology · 2013
Typearticle
Languageen
FieldEngineering
TopicOptical Network Technologies
Canadian institutionsMcGill University
Fundersnot available
KeywordsGuard intervalPhase-shift keyingBit error rateQuadrature amplitude modulationPhase noiseSubcarrierOrthogonal frequency-division multiplexingElectronic engineeringAlgorithmComputer scienceSymbol rateTelecommunicationsEngineeringChannel (broadcasting)

Abstract

fetched live from OpenAlex

We propose intra-symbol carrier phase recovery (IS-CPR) for reduced-guard-interval (RGI) CO-OFDM in order to compensate for the intra-symbol phase shift (ISPS) between subcarriers that is caused by the dispersion-enhanced phase noise (DEPN). We begin by proposing a pre-emphasized pilot subcarrier (PEPS) approach to reduce the pilot subcarrier overhead for the following IS-CPR algorithms. Then, we show a statistical analysis of the DEPN-induced ISPS between subcarriers within one symbol, which is related to the accumulated chromatic dispersion (CD). Next, three algorithms are proposed for IS-CPR including maximum-likelihood (ML) phase estimation, digital phase-locked loop (DPLL), and feedforward carrier recovery (FFCR) employing either the <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">M</i> th power scheme in case of QPSK modulation or the QPSK partitioning scheme for the 16-QAM case. The performance and complexity of these algorithms are compared. Through simulations, we show that in comparison to conventional common phase error (CPE) compensation, IS-CPR significantly improves the linewidth tolerance at 1 dB signal-to-noise ratio (SNR) penalty for a bit error rate (BER) = 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-3</sup> from 300 kHz to 2 MHz for 112 Gb/s systems (28 Gbaud QPSK) at 3200 km transmission distance, and from 70 kHz to 550 kHz for 448 Gb/s (56 Gbaud 16-QAM) systems at 1600 km transmission distance.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.523
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.010
GPT teacher head0.259
Teacher spread0.249 · 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