A low noise figure 2-GHz bandwidth LNA using resistive feedback with additional input inductors
Bibliographic record
Abstract
In this paper, an input inductive network for the wideband LNA is proposed. The two input inductors located in and out of the feedback loop are set respectively to combine with the conventional resistive feedback structure. Input matching and NF of the LNA can be optimized separately by varying the value of the two input inductors without significant influence from one to the other. The proposed cascode LNA was analyzed, designed, and fabricated in the IBM 0.13μm CMOS technology to verify the concept. A −10dB S11 is achieved in a wide range of frequency from 1GHz to 3GHz. Within this bandwidth, the LNA has a gain of 7.5dB and a minimum noise figure of 2.5dB while consumes a 7mW of power. The results indicate that the proposed input-network effectively alleviates the tradeoff between noise figure and bandwidth without requiring extra power consumption.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 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 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".