Architecture and Design of a New Non-Quadrature Vector-Sum Microwave Phase Shifter at 10 GHz With Maximum Residual Phase Error of 1.80°
Bibliographic record
Abstract
This paper presents the architecture, design, and simulation of a new vector-sum phase shifter for prospected use in applications that require low amplitude loss. The architecture is based on non-quadrature phase generation and synthesis. The phase generation is done by splitting the input signal into two equal-phase output vectors and delaying one signal vector to the other; while the phase synthesis is implemented by subjecting the vectors through path selection and variable amplification & attenuation before subtracting the different paths. A two-bit phase path selection was employed for achieving 360° of coarse & fine tuning. EM simulations of the phase shifter architecture was carried out using RT-Duroid 5880 specifications$(\varepsilon_{r}=2.2,\boldsymbol{\tan\delta=0.004)}$at center frequency of 10 GHz. A maximum phase error of$\mathbf{1.82^{\circ}}$was obtained for the entire interval of 360 degrees of phase shift. With less than$2^{\mathrm{o}}$of phase error, the proposed phase shifter architecture is feasible for millimeter-wave phase array beamforming applications; as it offers the possibility of lower power consumption with the use of lesser compartmental blocks (i.e. compared to a T-bridge phase shifter which uses a chain of multiple blocks that can lead to excessive losses of more than 30 dB).
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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) | 0.002 | 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".