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Record W2140556505 · doi:10.1109/jlt.2008.917332

Experimental Demonstration of a SAC-OCDMA PON With Burst-Mode Reception: Local Versus Centralized Sources

2008· article· en· W2140556505 on OpenAlexaff
Ziad A. El-Sahn, Bhavin J. Shastri, Ming Zeng, Noha Kheder, David V. Plant, Leslie A. Rusch

Bibliographic record

VenueJournal of Lightwave Technology · 2008
Typearticle
Languageen
FieldEngineering
TopicAdvanced Photonic Communication Systems
Canadian institutionsUniversité LavalMcGill University
Fundersnot available
KeywordsPassive optical networkTelecommunications linkNetwork topologyPower (physics)Computer scienceCLs upper limitsWavelength-division multiplexingElectronic engineeringTopology (electrical circuits)Bit error rateTelecommunicationsOptical line terminationAccess networkPower budgetComputer networkEngineeringPhysicsElectrical engineeringOpticsDecoding methodsWavelengthPower control

Abstract

fetched live from OpenAlex

In this paper, we demonstrate experimentally the uplink of a 7 times 622 Mb/s incoherent spectral amplitude coded optical code-division multiple access (SAC-OCDMA) passive optical network (PON) with burst-mode reception. We consider two network architectures: local sources (LS) at each optical network unit (ONU) versus a single source located at the central office. We examine both architectures over a 20-km optical link, as well as a reference back-to-back configuration. Our architectures can adopt two-feeder and single-feeder topologies; however, we only test the two-feeder topology and therefore the effect of Rayleigh backscattering is neglected. We also study the relative merits (cost and performance) of local sources versus centralized architectures. A penalty of less than 2 dB between the LS and the centralized light sources (CLS) architectures was measured at a bit error rate (BER) of 10-9under certain assumptions on the relative power of the sources. The power budget in the CLS architectures is more critical than in the LS architectures; extra splitting and propagation losses exist as the uplink travels through the network back and forth. Doubling the number of users while maintaining the same distance and source power in LS architectures imposes 3-dB additional losses, whereas for CLS architectures, there are 6-dB extra losses. CLS architectures can overcome these penalties using amplification at the central office. Alternately, central office amplification can be used to more than double the number of users in LS SAC-OCDMA PONs. A standalone (no global clock) burst-mode receiver with clock and data recovery (CDR), clock and phase alignment (CPA), and Reed-Solomon RS(255,239) forward-error correction (FEC) decoder is demonstrated. A penalty of less than 0.25 dB due to the nonideal sampling of the CDR is reported. The receiver also provides an instantaneous phase acquisition time for any phase step between consecutive packets, and a good immunity to silence periods. A coding gain of more than 2.5 dB was reported for a single-user system, and BER floors were completely eliminated. Error-free transmission (BER-9) for a fully loaded PON was achieved for the LS architecture as well as the CLS architecture. Continuous and bursty upstream traffic were tested. Due to the CPA algorithm, even with zero preamble bits we report a zero packet loss ratio (PLR) for up to four simultaneous users in case of bursty traffic, and more than two orders of magnitude improvement in the PLR for fully loaded PON systems.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.258
Teacher spread0.240 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations33
Published2008
Admission routes1
Has abstractyes

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