Nanoscale CMOS Transceiver Design in the 90–170-GHz Range
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/fnoise 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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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".