Analysis and design of a new fountain codec under belief propagation
Bibliographic record
Abstract
Error‐prone patterns have been extensively studied for low‐density parity‐check codes yet they have never been fully explored for generator‐based ‘Fountain codes’. It is shown here that these phenomena are related to certain combinatorial structures within the Tanner graph (TG) representation of the code, previously termed absorbing sets. The authors systematically define the ‘absorbing sets’ in the generator‐based TG of a code. They then demonstrate how these substructures are damaging to the ‘realised rate, delay’ and ‘decoding cost’ of Fountain codes particularly at low error rates. They further analyse the existence probability of certain absorbing sets and propose a new encoder/decoder pair forming a new family of Fountain codes. The authors experimental results show that these new codecs lead to improvements in all system features. Typical gains for Luby‐transform codes include 20 % reduction in the decoding complexity and simultaneous coding gains of 0.6 and 0.9 dB at bit error rates of 10 − 5 and 10 − 6 , respectively. As such, this work takes a step towards better rateless code design and construction.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".