Noise Analysis and Design Considerations for Equalizer-Based Optical Receivers
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Bibliographic record
Abstract
Optical receiver front ends that are intentionally designed to have a bandwidth low enough that significant inter-symbol interference (ISI) is introduced are becoming commonplace. Although the resultant ISI must be removed using an equalizer, the lower bandwidth allows for higher gain in the front-end's first stage, lower input-referred noise, and fewer gain stages. With fewer main-amplifier stages, power dissipation is reduced. The noise analysis of these front ends presents several challenges. This paper derives integrated input-referred noise for inverter-based shunt-feedback transimpedance amplifiers from first principles and highlights the importance of correctly estimating the gain and noise bandwidth of the receiver. The notion of the effective gain of the receiver is introduced, which is lower than the midband gain typically used in noise calculations. The analysis of the inverter-based TIA is used to discuss the important design tradeoffs depending on the type of equalizer used. Integrated input-referred noise is derived and compared for front ends using decision-feedback equalizers (DFEs), continuous-time linear equalizers, and feed-forward equalizers. The simulation results show that a DFE-based receiver achieves the lowest input-referred noise.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it