A V-Band 16% Efficiency Frequency Doubler-Based RF Beamforming Front-End Module for Vector Modulated Signal Transmission
Bibliographic record
Abstract
This paper presents a millimeter-wave frequency multiplier (FM)-based RF beamforming front-end (FE) suitable for high-frequency vector signal transmission. The design considerations (i.e., tuning range, phase resolution, and magnitude variation) of the phase shifter are discussed in the context of FM-based FE. These considerations guided the design of the proposed FE which incorporates an 8-bit phase shifter, a driver amplifier, and a frequency doubler with their matching networks co-designed to minimize the FE area. A proof-of-concept prototype is designed using 45-nm CMOS-SOI technology. The measurements conducted at 62 GHz output frequency showed an average conversion gain (CG) of 5.7 dB, a doubler drain efficiency of 22.7%, and an FE drain efficiency of 16%. When the phase is varied to cover the full 360° in a step of 2.8° with an RMS phase error of 0.57°, the CG deviated by a maximum of ±0.35 dB. Using a low-complexity digital pre-distortion technique, the designed FE maintained an error vector magnitude of -30 dB and an average drain efficiency of 6% when used to generate a 256-QAM 200 MHz orthogonal frequency division multiplexing vector modulated signal and the phase is varied to cover the full 360°.
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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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".