Digitally Assisted 28 GHz Active Phase Shifter With 0.1 dB/0.5° RMS Magnitude/Phase Errors and Enhanced Linearity
Bibliographic record
Abstract
This brief presents a new digitally assisted vector-summing phase shifter (DA-VSPS) featuring high accuracy and enhanced linearity. It begins by highlighting the RF performance degradation of traditional DA-VSPSs operating at millimeter-wave frequencies due to the large number of unit-cells and the significant underlying parasitics. Then, a new DA-VSPS topology is proposed to mitigate this source of performance degradation using analog variable-gain amplifiers with digitally assisted current sources. A study of the accuracy and linearity of the proposed DA-VSPS is conducted to inform the choice of the optimal parameters (number of unit-cells and load impedance) that maximize the RF performance while minimizing the implementation complexity. A proof-of-concept prototype was implemented in 45 nm silicon-on-insulator CMOS technology. The measurement results demonstrated a 1-dB RF bandwidth from 27 to 33 GHz, root-mean-square magnitude and phase errors of 0.1 dB and 0.5° to 0.6°, respectively, while covering 360° of phase shifts at 5° resolution. Furthermore, the measured group delay and input 1dB compression point are maintained within ± 4 ps and >2.2 dBm, respectively, at any phase shift settings.
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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 | 0.001 |
| 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 | 0.001 |
| 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".