A Min-Sum Iterative Decoder Based on Pulsewidth Message Encoding
Bibliographic record
Abstract
In this brief, we introduce a new iterative decoder implementation called pulsewidth-modulated min-sum (PWM-MS), in which messages are exchanged in a pulsewidth-encoded format. The advantages of this method are low switching activity, very low complexity check nodes, low routing congestion, and excellent energy efficiency. We implement a fully parallel PWM offset MS decoder for a (660, 484) regular (4, 15) low-density parity-check code with 4-bit quantization in 0.13-μm CMOS, with a core area of 5.76 mm2(4.24-mm2cell area or 556K equivalent and gates). In postlayout simulations, this decoder achieves an average information throughput of 5.71 Gb/s and an energy consumption of 65.8 pJ per information bit at a signal-to-noise ratio of 5.5 dB. Our results show a 21% reduction in area, a 0.6-dB improvement in coding gain, and an energy efficiency improvement of 19% over the comparable bit-serial MS decoder architecture. We also demonstrate 3-bit implementations, in which the coding gain is traded off for further improvements in throughput, area, and energy efficiency.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".