Broadband Low-Noise Amplifier With Fast Power Switching for 3.1–10.6-GHz Ultra-Wideband Applications
Bibliographic record
Abstract
A novel fast switching noise-cancelling low-noise amplifier (LNA) is presented in this paper using 0.13-μ m CMOS for 3.1-10.6-GHz ultra-wideband applications. A new noise-cancelling topology is employed to simultaneously achieve a sub-4-dB flat noise figure and a high gain of 16.6 dB for frequencies up to 10 GHz. Fast on and off power switching is achieved by bypassing the large dc-bias resistors that lead to long charging time constants, allowing the output voltage to settle within only 1.3 ns for switching frequencies as high as 200 MHz. The phase noise and jitter added by the switched LNA was characterized, and the measured output integrated rms jitter is about 750 fs from 10 Hz to 1 MHz, while the input integrated rms jitter is 420 fs. The circuit consumes 18 mW of dc power in the on state. When the circuit is switched on and off with a 50% duty cycle, the power consumption is less than 10 mW. It occupies an active chip area of less than 0.5 mm2.
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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) | 0.001 | 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) | 0.001 | 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 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".