Design and implementation of optoelectronic interfaces for high-speed burst-mode transmissions
Bibliographic record
Abstract
The popularity of internet and multimedia has greatly increased the demand for high-speed transmission networks. The next generation of optical networks will likely request fast packet switching to support multimedia applications. In fact, in such applications, the amplitude and phase of the receiver can be quite different from packet to packet due to different fiber attenuation and the chromatic dispersion caused by the variation of the transmitter’s wavelength. Link performance is strongly dependent on both the sensitivity and dynamic range of the receiver circuit. Although emerging lightwave communication technologies are bringing 10 Gb/s systems into commercial use [K. Yukio, A. Yuji, N. Kiyoski, K. Hiroyuki, and Y. Imai, IEEE Trans. Microwave Theory Tech. 43, 1916 (1995)], optoelectronic interfaces are still limiting factors for better performances. In this article, we address power penalty in high-speed burst-mode operation. Architectures applicable to high-speed systems and insensitive to parasitic input loading are proposed to overcome speed limitations at the receiver’s input. A 4.7 GHz bandwidth, a transimpedance of 43 dB Ω and an average input noise current density of 9 pA/Hz have been achieved in simulations with the single-ended version.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".