1.23-pJ/bit 25-Gb/s Inductor-Less Optical Receiver With Low-Voltage Silicon Photodetector
Bibliographic record
Abstract
This paper presents the design and measurement results of an inductor-less and power-efficient 25-Gb/s optical receiver in 65-nm TSMC technology. Furthermore, the design and characteristics of a novel 850-nm low-voltage silicon-on-insulator based all-silicon photodetector (Si-PD) are demonstrated. The proposed receiver front end consists of an inverter-based feedback transimpedance amplifier and three stages of inverter-based Cherry-Hooper post-amplifier. To this structure, local positive feedback and third-order interleaved active feedback are added to increase the bandwidth of the front end. Measurement results show that the receiver front end has a transimpedance gain of 69.4 dBQ, a bandwidth of 13.6 GHz, and an input-referred current noise of 3.28 μArms. It occupies only 0.0056 mm2 and consumes 30.8 mW at 1.1-V supply voltage. The proposed Si-PD has a responsivity of 0.05 A/W (at 850 nm), a dark current of 0.02 nA, and a bandwidth of 12.6 GHz at 0-V bias voltage. For a bit error rate of 10-12, the optical receiver with a wire-bonded Si-PD has a sensitivity of 46 and 54 μAp- p at data rates of 20 and 25 Gb/s, respectively, at a reverse-bias voltage of 0.41 V. The energy efficiency of the all-silicon 850-nm optical receiver is 1.23 pJ/bit at 25-Gb/s data rate. The receiver front end was also measured with an electrical input signal with supply voltages lower than 1.1 V. For an input sensitivity of 5 mVp-p, the receiver front end has energy efficiencies of 0.425 and 0.8 pJ/bit at data rates of 20 and 25 Gb/s, for supply voltages of 0.85 and 1 V, respectively.
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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 | 0.001 | 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) | 0.003 | 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".