Bibliographic record
Abstract
Multipulse pulse position modulation (MPPM) has been widely proposed to improve data rate over traditional pulse position modulation (PPM) in free-space optical communication systems. Encoders for MPPM are typically lookup-table-based, thus restricting the practical size of MPPM codebooks. Power-of-two-sized MPPM codebooks typically do not have an efficient soft-in soft-out decoder, making them poorly suited for concatenation with an outer code under iterative decoding. In this paper, a new coding technique based on constrained coding is introduced that allows construction of codes which have an efficient encoding algorithm. More importantly, these new codes are suitable for iterative soft-decision decoding in concatenation with an outer error-correcting code. Simulation results for both the Gaussian and Poisson channels show that a serial concatenation with an outer low-density parity-check code (LDPC) can achieve between 2 to 3 dB coding gain over comparable Reed-Solomon and LDPC-coded MPPM systems.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".