Bibliographic record
Abstract
Optical CDMA provides one avenue to sharing the vast bandwidth of optical fiber among a number of active users in a network. In this work we address two questions central to considering the areas of applicability of CDMA in optics: (1) How do we compare fairly optical CDMA codes of different families, and what do we conclude? (2) How do we compare optical CDMA performance with that of conventional optical WDMA? To answer the first question, we present a method of comparing optical CDMA codes of different families, sizes and weights. We outline why the traditional performance metric of bit-error rate versus number of simultaneous users is lacking and propose a different performance measure -- the peak throughput normalized with respect to the size of the code. This metric is used to show that optical-orthogonal codes (OOCs) with a weight of 4 perform best at low offered loads while OOCs with weight 5 should be used at higher offered loads. By applying the technique across different families of codes, we demonstrate that multi-wavelength OOCs (MWOOCs) perform better than both OOCs (by a factor of approximately 1.25) and asymmetric prime-hop codes (by a factor of approximately 3.5), over a wide range of offered loads. In answer to the second question, we present a comparison of the performance of optical code-division multiple-access (CDMA) systems with that of a wavelength-division multiple-access (WDMA) system. The multiple-access techniques are applied in a time-slotted broadcast local-area network. The utilization, defined as the throughput per unit of time-domain bandwidth expansion, and packet delay are used as metrics of performance. When more than seven wavelengths are available, optical CDMA systems using asymmetric prime-hop codes and all-optical signal processing are shown to have higher peak utilization and lower corresponding delay than a WDMA system with the same number of wavelengths. When the encoders/decoders operate at the chip rate, the utilization of optical CDMA exceeds that of WDMA at high offered loads; however, the peak utilization of the WDMA system is still superior.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".