Design and Test of a 175-Mb/s, Rate-1/2 (128,3,6) Low-Density Parity-Check Convolutional Code Encoder and Decoder
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> Low-density parity-check block codes (LDPC-BCs) are quickly becoming the forward error correcting code of choice for emerging communication standards. However, low-density parity-check convolutional codes (LDPC-CCs), the convolutional counterpart of LDPC-BCs, seem to be better suited in applications with streaming data or variable sized packets. A rate-1/2, (128,3,6) LDPC-CC ASIC has been implemented in 180-nm, 1.8-V CMOS technology. We present the VLSI architecture of a register-based LDPC-CC encoder and decoder that includes an on-chip, pseudo-random additive white Gaussian noise channel emulator. The decoder comprises a pipeline of ten identical processing units and attains up to 175 Mb/s of decoded throughput. </para>
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it