Bibliographic record
Abstract
As fibre-optic communication systems scale beyond one terabit per second, conventional CMOS-based digital-to-analog and analog-to-digital converters increasingly struggle to meet the required bandwidth and power efficiency. Analog time-interleaving has emerged as a viable solution for extending symbol rates without the complexity and power overhead of digital processing at ultra-high speeds. This thesis investigates broadband analog time-interleaving as a technique for extending effective sampling rates while maintaining energy-efficient operation. A novel analog multiplexer architecture is designed and implemented in a 22 nm FDSOI CMOS process, leveraging the technology’s back-gate biasing capability to enhance performance and allow for a built-in equalizer. The circuit achieves operation up to 192 GBaud using PAM-4 modulation, the highest symbol rate reported for an AMUX in any technology to date. It exhibits a spurious-free dynamic range of 32 dB for a 1 GHz sinusoidal input and consumes a total of 185 mW, with only 64 mW attributed to the novel merged AMUX-equalizer stage. The design is validated through schematic simulations, full layout implementation, post-layout verification, and experimental measurements. The results demonstrate the feasibility of using advanced CMOS nodes for broadband time-interleaving, offering a compelling alternative to traditional high-speed technologies such as SiGe BiCMOS and InP HBT. This work contributes a scalable and energy-efficient solution for future high-speed optical transceivers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".