A <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>Q</mml:mi></mml:math>-Enhanced 3.6 GHz, Tunable, Sixth-Order Bandpass Filter Using 0.18 <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>μ</mml:mi></mml:math>m CMOS
Bibliographic record
Abstract
An experimental filter was designed to operate at 3.6 GHz using mainstream 0.18 <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>μ</mml:mi></mml:math>m CMOS. In the design, the <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>Q</mml:mi></mml:math>-enhancement technique was used to overcome the low-<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>Q</mml:mi></mml:math> characteristics of the CMOS on-chip inductors. A sixth-order bandpass filter with a wide passband and a high image rejection was built by cascading three stages of second-order <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>Q</mml:mi></mml:math>-enhanced filters. A combination of three biquads with offset in center frequency provides wider tuning frequency and bandwidth. This high-performance filter provides a 340 MHz tunable center frequency around 3.6 GHz, an image rejection of 50 dB and a tunable <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>Q</mml:mi></mml:math> from 25 to 50 for a bandwidth adjustment from 95 MHz to 35 MHz. The filter achieves an 18 dB voltage gain while consuming 130 mW of power at 1.8 V DC supply. The chip occupies an area of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mn>900</mml:mn><mml:mo>×</mml:mo><mml:mn>900</mml:mn><mml:mi>μ</mml:mi><mml:msup><mml:mtext>m</mml:mtext><mml:mn>2</mml:mn></mml:msup></mml:mrow></mml:math> including all the required bonding pads. The design provides a simple architecture to simplify tuning scheme for both frequency and bandwidth for practical use. The tunable ability of the design could be exploited in further study to be used as a channel-select filter in the gigahertz range.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".