Miniaturized spoof SPPs filter based on multiple resonators or 5G applications
Bibliographic record
Abstract
This paper presents a novel and compact band-pass filter based on spoof surface plasmon polaritons (SSPPs) concept for 5G applications. In the first place, an SSPPs unit cell including L-shaped grooves and its equivalent circuit model are introduced. The obtained results from dispersion analysis shows that cut-off frequency of the cell can be considerably decreased thanks to its geometrical configuration. In the second place, a miniaturized SSPP transmission line (TL) consisting of the proposed unit cell with cut-off frequency of 29.5 GHz is designed. Two mode convertors have been employed for efficient connection between coplanar waveguides and SSPP TL. Moreover, a new method based on loading one unit cell of SSPP TL by stub resonators is proposed in order to block a specific frequency band. An equivalent circuit model for the cell with the resonators is proposed to predict rejected frequency range. Thereafter, as an example of our method, a SSPPs filter operating at 26.5-29.5 GHZ is designed by means of connecting stub resonators with different lengths to provide close resonance frequencies. The circuit model, full wave simulation, and measurement results are in a good agreement. The results of proposed groundless SSPP TL and filter structures are promising to make groundless 5G applications possible.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".