Design Methodology of a High-$Q$ Tunable Coaxial Filter and Diplexer
Bibliographic record
Abstract
Any filter of order N can be readily tuned for a constant absolute bandwidth (BW) using 2N + 1 independent tuning elements. This significantly increases the size and the cost, and also adds to the complexity of the tuning control mechanism. This article demonstrates the feasibility of realizing a highQ tunable coaxial filter, which is tuned by a single rotational tuning element irrespective of the filter order. The proposed filter has low variations in the absolute BW and insertion loss (IL) over a relatively wide tuning range. A prototype four-pole filter is developed at 2.5 GHz with a fractional BW of 4% to verify the concept. The measured tuning range of the filter is 20%, within which the BW variation is better than ±10% and IL variation is better than 0.05 dB. The proposed concept is easily expandable to filters with higher order. Furthermore, the concept is adopted to design a tunable diplexer which can be tuned using a single tuning mechanism. The proposed highQ tunable filter is promising for use in the frequency-agile communication architecture at the cellular base-station and aerospace applications.
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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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".