Design techniques for high-speed low-power wireline receivers
Bibliographic record
Abstract
High-speed data transmission through wireline links, either copper or optical based, has become the backbone for modern communication infrastructure. Since at multi-Gb/s data rates the transmitted signal is attenuated and distorted by the channel, sophisticated analog front-end and/or digital signal processing are required at the receiver (RX) to recover data and clock from the received signal. In this thesis, both analog- and digital-based receivers are investigated, and power-reduction techniques are exploited at both system- and circuit levels. A speculative successive-approximation register (speculative/SAR) digitization algorithm is proposed for use at the receiver front-end of digital receivers that combines equalization and data recovery with the digitization step at the front-end analog-to-digital converter (ADC). Furthermore, architecture for quadrature clock generation is proposed which is of use in both analog and digital receivers. Then, an analog clock and data recovery (CDR) architecture suitable for high data rates (e.g., beyond 10 Gb/s) is proposed that utilizes a wideband data phase generation technique to facilitate mixer-based phase detection. The CDR architecture is implemented and experimentally validated for a 12.5 Gb/s system. Finally, a mixed-mode hardware-efficient CDR architecture is proposed that exploits both analog and digital design techniques to reach a robust operation suited for long-haul optical link communications. Proof-of-concept prototypes of the proposed RX architectures are designed and implemented in 65 nm and 90 nm CMOS processes. The prototypes are successfully tested. Note that although individual performance merits of the each prototype may not necessarily outperform that of the state-of-the-art, however, the prototypes confirm the feasibility of the proposed structure. Furthermore, the proposed architectures can be used at higher data rates particularly if more advanced technologies with higher device transit frequency, (fT), is used.
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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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".