A Reconfigurable Low-Voltage and Low-Power Millimeter-Wave Dual-Band Mixer in 65-nm CMOS
Bibliographic record
Abstract
In this paper, we propose, investigate, and demonstrate a reconfigurable low-voltage and low-power millimeter-wave mixer in a 65-nm CMOS, which can be switched as either a subharmonic mixer (SHM) or a fundamental mixer (FM) for the dual-band applications. Based on a modified Gilbert mixer topology, the proposed CMOS mixer can operate at a low supply voltage and low local oscillator (LO) pumping power while providing good performance in both SHM and FM modes. To the best of our knowledge, this is the first reported Gilbert SHM based on the stacked switching quads in a low-voltage CMOS technology. Under 1-V supply voltage and -3-dBm LO pumping power, the measured conversion gain (CG) of the proposed CMOS mixer is -4.8 ± 1.5 dB from 34 to 56 GHz and -0.1 ± 1.5 dB from 17 to 43 GHz in the SHM and FM modes, respectively. The measured double-sideband (DSB) noise figure (NF) is 18.5-20 dB from 37 to 49 GHz and 12.4-14 dB from 17 to 35 GHz in the SHM and FM modes, respectively. The measured input third-order intercept point (IIP3) is 2.9 and 3.4 dBm, respectively, for the SHM and FM modes at the LO frequency of 22 GHz. In addition, the total dc power consumption of the proposed mixer including output buffers is 7 mW in both the operation modes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".