Performance–Complexity–Latency Trade-offs of Concatenated Codes for High-Throughput Optical Communication Systems
Bibliographic record
Abstract
This thesis explores the performance-complexity-latency trade-offs of concatenated coding systems for high-throughput optical communication systems. In particular, outer Reed--Solomon (RS) codes concatenated with inner Bose--Ray-Chaudhuri--Hocquenghem (BCH) codes are studied. The inner BCH codes are decoded using either a hard-decision (HD) or a soft-decision (SD) decoder, while the outer RS codes are decoded using an HD decoder only. For the concatenated RS-HDBCH coding system, the binary symmetric channel model is assumed. For the concatenated RS-SDBCH coding system, the additive white Gaussian noise channel with four-level pulse amplitude modulation (PAM4) is assumed. Both bit-interleaved coded modulation (BICM) and multilevel coding (MLC) coded modulation architectures are considered in the case of RS-SDBCH. For a fixed interleaving scheme between the outer RS and inner BCH codes, a generating function is used to describe the interaction between bit errors in the BCH codewords and symbol errors in the RS codewords. The generating function gives rise to computationally tractable analytical and semi-analytical formulas that accurately estimate the frame error rate arising at the output of the concatenated RS-BCH decoder, eliminating the need for time-consuming Monte Carlo simulation. These formulas are used to search a large space of codes to find those achieving good trade-offs of performance (measured by the gap to the hard-decision Shannon limit and PAM4-constrained Shannon limit in the case of RS-HDBCH and RS-SDBCH, respectively), complexity (measured by the number of elementary decoding operations per decoded information bit), and latency (measured by overall block length). Finally, a hybrid soft/hard-decision iterative decoding scheme between the outer RS and inner BCH codes is considered. In this scheme, the inner BCH codes are decoded using an SD decoder only on the first decoding round, while an HD decoder is used for the subsequent decoding rounds. By allowing additional decoding iterations, the performance of rate-0.88 RS-BCH codes can be improved by up to 0.4 dB with only a modest increase in decoding complexity.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".