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Record W1985528294 · doi:10.1109/bsc.2010.5472957

Coding for MPPM-like systems

2010· article· en· W1985528294 on OpenAlexaff
Siyu Liu, Frank R. Kschischang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOptical Network Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComputer scienceCoding gainDecoding methodsCoding (social sciences)Pulse-position modulationDuty cycleAlgorithmEncoding (memory)Block codeElectronic engineeringTelecommunicationsPulse-amplitude modulationMathematicsPulse (music)EngineeringElectrical engineeringVoltage

Abstract

fetched live from OpenAlex

Multipulse pulse position modulation (MPPM) has been widely proposed to improve data rate over the traditional pulse position modulation (PPM) in free-space optical communication systems. However, there is no known efficient method of encoding MPPM codewords. Furthermore, MPPM is not the optimal coding scheme (in terms of data rate) given the two main constraints of optical systems (duty cycle and zero runlength). In this paper, a new coding technique based on constrained coding is introduced that allows construction of codes which achieve considerable rate gain over comparable MPPM systems. In addition, our new codes allow for convenient concatenation with an outer code and are suitable for iterative decoding. Simulation results show that these codes can achieve a 6 dB coding gain over comparable MPPM 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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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 science0.0000.001
Research integrity0.0010.001
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 head0.009
GPT teacher head0.203
Teacher spread0.194 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations4
Published2010
Admission routes1
Has abstractyes

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