Low-Complexity Zipper-LDPC and Low-Latency Zipper-BCH Concatenated Codes
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
A novel concatenated forward error correction (FEC) scheme is proposed that consists of an inner zipper framework with low-density parity-check component codes and an outer zipper framework with BCH component codes. The proposed soft-decision inner codes have a universal, flexible, and implementation-friendly structure with low decoding complexity. The inner code is error-reducing, tasked with reducing the error rate on bits passed to the outer hard decision code below its threshold. The proposed outer codes have ultra-low overhead and are designed to have small decoding memory and latency. Computer simulations show that the proposed zipper-BCH codes can reduce the decoding latency and required memory by up to a factor of 30, compared to the conventional zipper codes, while maintaining a minimal performance loss. The proposed scheme is considered with higher-order modulation with both multi-level coding and bit-interleaved coded modulation. Simulations show that the concatenated FEC scheme can provide a 0.1 dB gain over the state-of-the-art FEC designs, making it a highly attractive FEC solution for high-throughput optical communication systems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| 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