A CMOS Finite Impulse Response Filter With a Crossover Traveling Wave Topology for Equalization up to 30 Gb/s
Bibliographic record
Abstract
This paper describes a fully differential 3-tap finite impulse response filter in 90-nm CMOS. A traditional traveling wave filter topology is modified to alleviate its inherent delay-bandwidth-gain tradeoffs. Each tap gain is comprised of two transconductors whose outputs superimpose with the same group delay, similar to a distributed amplifier. This doubles the bandwidth of the filter for a given tap spacing and gain. Digital control is provided for the tap gains, an integrated pre-amplifier, and tuning varactors. Coupled differential spirals are used in the delay lines to help the design fit into an area 600 /spl mu/m/spl times/500 /spl mu/m. A 1-V supply voltage and 25-mW power consumption are enabled by the use of parallel differential pairs for sign control of the transconductances instead of Gilbert cell amplifiers. The input return loss is better than 16 dB and the output return loss is better than 9 dB up to 30 GHz. Equalization of NRZ data over a coaxial cable channel was demonstrated up to 30 Gb/s, making it faster than any previously reported CMOS equalizer.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".