Highly reconfigurable single-ended low noise amplifier for software defined radio applications
Bibliographic record
Abstract
A reconfigurable low noise amplifier with variable gain, bandwidth and center frequency is described. In order to achieve this degree of reconfigurability, this amplifier employs variable-bias active shunt feedback input matching, with a switchable capacitive load and a Q-enhancing negative g <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</sub> circuit in parallel with the load. This design also features a noise cancelling technique, which helps to eliminate noise contributions from the primary gain FETs and simultaneously enhance the gain. This design was built on IBM's CMOS 0.13μm process through MOSIS and was designed for a 1.2V supply. This LNA has a min-to-max 3dB bandwidth ratio of approximately 3.1 while achieving a noise figure as low as 2.5dB, less than -10dB return loss, and IIP3 as high as -0.9dBm at low gain.
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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".