A Compact, High Tuning Accuracy and Enhanced Linearity 37-43 GHz Digitally-Controlled Vector Sum Phase Shifter
Bibliographic record
Abstract
This paper presents a compact digitally controlled vector sum phase shifter (DC-VSPS) capable of precise gain and phase control across a wide bandwidth. The DC-VSPS utilizes a pair of differential variable gain amplifiers (VGAs) designed to optimize gain and phase tuning accuracy. Moreover, it incorporates differential transformers-based output combiner and input quadrature hybrid, enhancing integration, bandwidth, and matching performance. A 6-bit DC-VSPS prototype was successfully designed and fabricated using the 45 nm silicon-on-insulator (SOI) CMOS technology, occupying a minimal core area of $0.084 \mathrm{~mm}^{2}$. Experimental results demonstrate an excellent tuning range of 360° for phase control with a resolution of 6 bits and 14 dB for gain control with 1 dB resolution. Furthermore, comprehensive measurements indicate excellent performance over the frequency range of 35-43 GHz, with total root-mean-square (RMS) phase error, total RMS gain error, and group delay variation all within 1.5°, 0.24 dB, and ±12 picoseconds, respectively. The prototype also exhibits input-referred 1dB gain compression power levels exceeding 4 dBm and input-output return losses better than 9 dB across the entire bandwidth.
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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 | 0.001 |
| 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".