Reconfigurable Impedance Matching Network for 5G Mid-Band Utilizing Phase-Change Materials
Bibliographic record
Abstract
In this paper, we present a phase-change, monolithically integrated reconfigurable impedance matching network (IMN) for the 5G mid-band. The IMN features an innovative design with 4-bit phase-change capacitor banks seamlessly integrated within the ground planes of co-planar waveguides (CPW), enabling compactness and high capacitance tuning range. The reconfigurable capacitors are controlled by miniaturized and integrated capacitor bank bits situated on both sides of the CPW. The fabricated device demonstrates a capacitance tuning range of 0.2 to 2.5pF, with a high Q-factor and no self-resonance up to 7GHz. The RF performance of the phase-change switches shows a loss of less than 0.2dB and an isolation greater than 30dB across a frequency range of 2 to 7GHz. The proposed reconfigurable IMN offers promising potential for adaptive and efficient radio frequency (RF) front-ends in modern wireless communication systems.
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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) | 0.001 | 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".