High-gain dual-band antenna with independent frequency operation for Sub-6 GHz and millimeter-wave applications
Bibliographic record
Abstract
This work presents an innovative dual-band hybrid antenna designed to achieve high gain and superior isolation, catering to both microwave and millimeter-wave applications. The proposed design integrates a cylindrical dielectric resonator antenna (CDRA) for the microwave band and patch ring resonators for the mm-wave band, providing distinct and optimized operation in each frequency range. The antenna design incorporates multiple stages: initially, the CDRA is tailored for efficient microwave performance; next, the patch resonators are configured for mm-wave operation. These components are then combined strategically to ensure compatibility and minimal interference between bands. To enhance the antenna’s functionality, selective filters are applied—specifically, a Low Pass Filter (LPF) for the microwave band and a Band Pass Filter (BPF) for the mm-wave band—mitigating harmonic distortion and improving spectral purity. Additionally, shorting pins are introduced to boost isolation levels between the bands. The resulting antenna achieves notable performance metrics, including bandwidths of 11.7% at 5.8 GHz and 14.3% at 28 GHz, with maximum realized gains of 12.3 dBi and 17.2 dBi, respectively. It also demonstrates exceptional isolation, surpassing 54 dB and 51 dB for the microwave and mm-wave bands. The innovative integration of these design elements enables independent frequency responses, making the proposed antenna a compelling solution for next-generation dual-band 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) | 0.001 | 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 | 0.003 |
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".