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Record W2129949766 · doi:10.1109/icc.2009.5198829

Coded Pulse-Position Modulation for Free-Space Optical Communications

2009· article· en· W2129949766 on OpenAlexaff
Trung T. Nguyen, Lutz Lampe

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicError Correcting Code Techniques
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPulse-position modulationComputer scienceLow-density parity-check codeDecoding methodsCoding (social sciences)Noisy-channel coding theoremConstellation diagramAlgorithmFigure of meritTransmission (telecommunications)Modulation (music)Bit error rateParity bitElectronic engineeringTelecommunicationsPulse-amplitude modulationMathematicsPulse (music)PhysicsError floorDetectorEngineering

Abstract

fetched live from OpenAlex

Multilevel (Q-ary, Q > 2) pulse-position modulation (Q-PPM) with direct detection is a very popular transmission method for power-efficient free-space optical communication systems. The combination of Q-PPM with error-control coding is an effective means to further improve power efficiency. In this paper, we study the application of the multilevel coding (MLC) paradigm to Q-PPM transmission. In particular, we devise a powerful coded Q-PPM scheme which is a simplified version of MLC and which we refer to as reduced-level MLC (RL-MLC). We show how to design and optimize RL-MLC for Q-PPM when using constellation-constrained capacity as the pertinent figure of merit. Furthermore, we provide simulative evidence that RL- MLC with off-the-shelf low-density parity-check codes (LDPC) closely approaches its corresponding capacity limit. For 64-PPM, RL-MLC with only two levels achieves practically the same performance as that of bit-interleaved coded modulation with iterative decoding (BICM-ID), which involves a more difficult design procedure.

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 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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.822
Threshold uncertainty score0.345

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 science0.0010.000
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 head0.033
GPT teacher head0.310
Teacher spread0.277 · 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 teacher head, 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
Published2009
Admission routes1
Has abstractyes

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