A Q- and bandwidth-enhancing design technique for active inductors using parasitic cancellation
Bibliographic record
Abstract
This paper presents the design technique and detailed equations of a high frequency, high-Q, active inductor (AI) that can be designed for frequencies above 6 GHz using non-minimal-length CMOS technologies, e.g. 130 nm CMOS, and used for industry because of the bias controls available in the topology. The design is achieved via a parasitic cancellation technique. An inductance of 2.89 nH is achieved at 6.5 GHz with a Q of 69. The designed active inductor is then used to obtain high-gain, narrowband tuning and an output matching element at or above 6.5 GHz using this technology. Although this AI design is used single-endedly in this work, it can be used differentially as well since the design is fully bi-directional. The inductor less LNA parameters at 6.5 GHz: S21 of 18 dB, NFmin of 3.22 dB, NF of 6 dB and S22 less than -15 dB with only 6.4 mW (plus 2.5 mW for narrow-band output match) power consumption for 1.2 V supply.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".