Nanoscale CMOS Transceiver Design in the 90–170-GHz Range
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Bibliographic record
Abstract
This paper reviews recent research conducted at the University of Toronto on the development of CMOS transceivers aimed at operation in the 90-170-GHz range. Unique nanoscale CMOS issues related to millimeter-wave circuit design in the 65-nm node and beyond are addressed with an emphasis on transistor and top-level layout issues, low-voltage circuit topologies, and design flow. A Doppler transceiver and two receivers fabricated in a 65-nm GPLP CMOS technology are described, along with a single pole, double throw antenna switch with better than 5-dB insertion loss and 25-dB isolation in the entire 110-170-GHz band. The first receiver has an IQ architecture with a fundamental frequency voltage-controlled oscillator, and is intended for wideband passive imaging applications at 100 GHz. The measured noise figure and downconversion gain are 7-8 and 10.5 dB, respectively, while the 3-dB bandwidth extends from 85 to 100 GHz. The second receiver has double-sideband architecture, operates in the 135-145-GHz range (the highest for CMOS receivers), and features an 8-dB gain LNA, a double-balanced Gilbert cell mixer, and a dipole antenna. The 90-94-GHz Doppler transceiver, the highest frequency reported to date in CMOS, is intended for the remote monitoring of respiratory functions. A Doppler shift of 30 Hz, produced by a slow-moving (4.8 cm/s) target located at a distance of 1 m, was measured with a transmitter output power of approximately + 2 dBm and a phase noise of -90 dBc/Hz at 1 MHz offset. The range correlation effect is demonstrated for the first time in CMOS by measuring the phase noise of the received baseband signal at 10-Hz offset, clearly indicating that 1/ <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">f</i> noise has been canceled and it does not pose a problem in short-range applications, where neither a phase-locked loop nor a frequency divider are needed.
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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 | 0.001 | 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 | 0.001 |
| 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 it