A comparative study of low-power CMOS Gilbert mixers in weak and strong inversion
Bibliographic record
Abstract
This paper presents a comparative study of 2.4 GHz double-balanced Gilbert mixers with devices operating in both weak and strong inversion. The current drawn from the supply voltage by the mixers in both weak and strong inversion is chosen to be less than 100 μA through proper biasing and sizing. Two Gilbert mixers are designed in IBM CMRF8SF-0.13μm 1.2V CMOS technology and analyzed using Spectre from Cadence Design Systems with BSIM4 models. The key parameters of the mixers are compared. Simulation results demonstrate that the power consumption of the mixer in weak inversion can be lowered to a few μW. This is at the cost of other performance such as IIP3, P1dB, and conversion gain. The power consumption of the Gilbert mixer is significantly lower as compared with that of the reported mixers in weak inversion. The other performance parameters of the Gilbert mixer in weak inversion are comparable to those of the reported mixers in weak inversion.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".