Efficient Low-Power Microwave Readout Circuit in 180 nm CMOS for Wearable Electronics
Bibliographic record
Abstract
The integration of microwave sensors and CMOS technology contributes to the development of wearable electronics to support small form factor and low power devices. This paper presents a unique microwave readout integrated circuit incorporated with a split ring resonator (SRR), particularly designed for gas monitoring in wearable electronics. The readout circuit is composed of a cross-coupled LC oscillator and an RF-to-DC converter. The LC oscillator naturally excites the SRR at the sensor's operating frequency, eliminating the need for the bulky vector network analyzer. The RF output of the SRR is regulated to a measured DC voltage level using the RF-to-DC converter. This DC voltage can then be used to power up the ADC or digital block in the wearable electronic device. The monolithic microwave readout circuit has been designed, simulated and implemented in TSMC 180 nm CMOS, occupying an active area of 0.108 mm2and consuming a low power of 777.1 µW obtained from post-layout simulation at a supply voltage of 1.5 V. These characteristics make the microwave readout circuit suitable for integration in wearable electronics.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".