An Ultra-Low-Power Wideband Inductorless CMOS LNA With Tunable Active Shunt-Feedback
Bibliographic record
Abstract
This work presents and analyzes the design of a 1-V ultra-low power, compact, and wideband low-noise amplifier (LNA). The proposed LNA uses common-gate (CG) NMOS and PMOS transistors as input devices in a complementary current-reuse structure. Low power input matching is achieved by employing an active shunt-feedback architecture while the current of the feedback stage is also reused by the input transistor to improve the current efficiency of the LNA. A forward body biasing (FBB) scheme is exploited to tune the feedback coefficient. The complementary characteristics of the input stage leads to partial second-order distortion cancellation. The proposed inductorless LNA is implemented in an IBM 0.13-μm 1P8M CMOS technology and occupies only 0.0052 mm2. The measured LNA has a 12.3-dB gain 4.9-dB minimum noise figure (NF) input referred third-order intercept point (IIP3) of -10 dBm and 0.1-2.2-GHz bandwidth (BW), while consuming only 400 μA from a 1-V supply.
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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) | 0.000 | 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".