Tunable Diplexer With Identical Passband and Constant Absolute Bandwidth
Bibliographic record
Abstract
Frequency-adaptive bandpass diplexer (FA-BPD) with constant absolute bandwidths (ABWs) and two identical passbands at every state is the most useful duplexing tunable filter for the smart frequency-division duplex (FDD) system. However, it is widely considered a challenge. In this article, we propose a new synchronously tuned trimode resonator (STTR) to achieve such a type of FA-BPDs. The proposed STTR has three flexible resonant modes that are able to be synchronously tuned by only one bias with the predefined frequency spacings. The spacings between every two tunable resonant frequencies can be precisely controlled as desired. Consequently, the resultant tunable filters can be implemented with different constant ABWs and at the different center frequency, which makes it possible to achieve two frequency-adaptive bandpass filters (FA-BPFs) at different frequency ranges but with the same ABW. Based on the proposed STTR, a three-pole FA-BPF with nearly 250-MHz ABW is examined. Using the FA-BPF as basic building blocks, a 1.5-3.5-GHz FA-BPD with identical passband and constant ABW is developed finally. The simulation and measurement results confirm the proposed design method and also exhibit the merits, such as low loss, simple design, wide frequency tuning range with synchronous passband.
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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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".