High-Efficiency Wideband Rectifier for Single-Chip Batteryless Active Millimeter-Wave Identification (MMID) Tag in 65-nm Bulk CMOS Technology
Bibliographic record
Abstract
This paper presents the development and demonstration of a high-efficiency rectifier for millimeter-wave-to-dc energy conversion. It is a critical circuit block that renders possible the use of a single CMOS chip die with no substrate and wiring, as the implementation of a batteryless, yet active tag for next-generation high data-rate millimeter-wave identification technologies. We also propose an architecture of a reader-tag system that addresses the underlying technical challenges. The rectifier is based on a differential drive cross-coupled topology that has been shown to work at UHF frequencies only so far. In this paper, we investigate significant challenges in implementing this topology at millimeter-wave frequencies with good power conversion efficiency (PCE). The analyses, design, and results presented in this work demonstrate the feasibility of achieving this by minimizing simultaneously the small on-resistance and the reverse leakage current in the MOS transistors, and by reducing losses and parasitic capacitances through proper transistor sizing and layout optimization. Using a standard 65-nm bulk CMOS process, a chip was designed, fabricated, and tested under different input and output loading conditions. The rectifier exhibits an overall PCE of 20% at 24 GHz, 18% at 35 GHz, and 11% at 60 GHz under RF available driving power of 6, 6, and 3 dBm, respectively, and output load resistance of 1, 1, and 2 kΩ, respectively. These PCE performances at millimeter-wave frequencies have never been reported in the literature.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".