A high IIP3 6.5 mW self-biased 0.3–3 GHz small area LNA
Bibliographic record
Abstract
This paper presents a 300 MHz to 3 GHz Low-Noise Amplifier (LNA) with high HP3 and one of the smallest silicon area we could find. It is based on a single amplifier, where it is systematically optimized to achieve better results than more complex noise canceling topologies, thus, saving area and power consumption. A CMOS inverter with resistive feedback where transistors are self-biased in strong inversion is designed and optimized for low NF and high IIP3 and then the feedback resistor is calculated for input impedance matching. The post-layout simulation results in a 130 nm process show for the entire bandwidth a voltage gain around 12 to 15 dB, a NF <; 3.6 dB, a Sii of -15.2 to -10.5 dB, HP3 of 4.7 to 5.3 dBm, total area of 40 um × 30 um and power consumption of 6.5 mW under 1.2 V supply. Monte Carlo simulations for 1000 samples show IIP3 of 3.3 to 6 dBm with σ of 0.48 dBm.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".