Trellis-based iterative decoding of block codes for satellite ATM
Bibliographic record
Abstract
In this paper, block turbo codes (BTCs) with trellis-based decoding are proposed for use in digital video broadcasting-return channel via satellite (DVB-RCS) for ATM transmission. Reed-Muller (RM) codes are used as the component codes. The BTCs are shortened in order to accommodate a satellite ATM cell. It is shown that different shortening patterns can be used. In some cases, the codes have unequal error protection (UEP) property. In order to test the suitability of the proposed coding scheme from a practical point of view, the effect of channel impairment, channel signal to noise ratio (SNR) mismatch, is investigated. Simulation results for RM-turbo codes and shortened turbo codes are presented over AWGN and Rayleigh-fading channels. The performance of the shortened codes with different shortening patterns and with the effect of channel SNR mismatch are shown.
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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 | 0.001 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".