A 10-Gb/s −18.8 dBm Sensitivity 5.7 mW Fully-Integrated Optoelectronic Receiver With Avalanche Photodetector in 0.13-$\mu$ m CMOS
Bibliographic record
Abstract
Avalanche photodetectors (APDs) improve the sensitivity of optoelectronic (O/E) receivers (RXs) due to their high multiplication gain and responsivity. When implemented monolithically with a CMOS transimpedance amplifier (TIA) on the same chip, they provide further advantages, such as low cost and reduced parasitics. However, APDs require high bias voltages, are sensitive to variations in operating conditions, and have a limited gain-bandwidth product. This paper presents an 850 nm APD implemented in a standard 0.13-μm CMOS process with a responsivity of 3.92 A/W and a large-signal -3 dB bandwidth of 3.5 GHz. Advantages of on-chip integration with a TIA are described and a noise-canceling active balun following the single-ended TIA is presented. The O/E-RXs front-end achieves a measured sensitivity of -18.8 dBm, the best-reported among 10 Gb/s linear CMOS TIAs operating at 850 nm. The energy/bit is 0.57 pJ/b. An on-chip voltage booster is described and implemented to generate a large APD bias using nominal CMOS voltage supplies. A modified hill-climbing algorithm is also presented that can enable bias stabilization for the voltage booster and the optoelectronic front-end for a complete all-bulk-CMOS implementation.
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".