A high-speed analog min-sum iterative decoder
Bibliographic record
Abstract
Current-mode circuits are presented for implementing analog min-sum (MS) iterative decoders. Proposed circuits are devised based on current mirrors. Therefore, in any fabrication technology that accurate current mirrors can be designed, analog MS decoders can be implemented. The functionality of the proposed modules was verified by implementing an analog MS decoder for a (32,8,10) regular LDPC code in 0.18-mum CMOS technology. In low signal to noise ratios when the circuit imperfections are dominated by the noise of the channel, the measured error correcting performance of this chip in steady-state condition surpasses that of the conventional MS decoder, and is close to the performance predicted by the earlier work on the dynamics of the continuous-time analog decoding by Hemati and Banihashemi, ISIT2004. At a throughput of 24 Mb/s, loss in the coding gain compared to the conventional MS decoder at BER of 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-3</sup> is about 0.3 dB. To the best of our knowledge, this decoder has the highest throughput and the lowest power/speed ratio among the reported analog CMOS iterative decoders
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".