Design and Packaging Analysis of a Ku Band High Gain GaAs MMIC LNA
Bibliographic record
Abstract
A Ku band high gain low noise amplifier (LNA) designed using the$0.15 \mu ~\mathrm{m}$GaAs pHEMT process is presented in this paper. Three types of connections between the MMIC (monolithic microwave integrated circuit) LNA chip and the input port are compared in terms of their loss and noise contribution. To achieve a very low noise figure, a gold bonding wire is used as a series matching inductor in the input matching circuit due to its minimal loss. The tolerance of the LNA related to the wire shape variation is also studied. EM-circuit co-simulation analysis of the LNA package is also carried out to detect higher mode resonances before fabrication. This MMIC LNA is designed, fabricated and packaged in a gold-plated chassis. The whole LNA module is measured through a coaxial system from 9 to 18 GHz. The gain ranges from 35 to 39.5 dB and the noise figure is lower than 1.75 dB. By de-embedding the noise contribution of the RF connector, the noise figure of the MMIC chip is lower than$\mathbf{1.26~ d B}$from$\mathbf{9}$to 18 GHz. Compared with other reported LNAs using a similar GaAs MMIC process in similar frequency bands, the presented LNA chip and module shows superior noise figure at room temperature.
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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 | 0.001 | 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".