Polarisation reconfigurable anisotropic dielectric resonator antenna
Bibliographic record
Abstract
A novel polarization reconfigurable anisotropic dielectric resonator antenna (ADRA) is presented utilizing a new modulation scheme to exploit the degree of freedom in the polarization domain. The ADRA comprises periodic assembly dielectric resonators with two different dielectrics constant, equal in size, a vertically positioned metal strip, one varactor diode, and six PIN diode switches. The modulation scheme utilizes the tilt angle and axial ratio (AR) of a wireless signal to convey additional information, enabling the realization of different working modes ranging from circular polarization (CP) to nearly linear polarization (LP). The proposed modulation scheme yields significantly better bit error rate (BER) performance and higher spectral efficiency in bits/s/Hz/antenna. Additionally, the paper presents an antenna design capable of generating an arbitrary polarization state, highlighting the system benefits of polarization modulation. Post-fabrication, the proposed approach is validated by comparing simulated and measured results. The proposed antenna provides a total efficiency higher than 93% in the desired frequency bands and consistent gain at approximately 7.64 dBi and 7.09 dBi at 3.8 GHz, with the impedance matching bandwidth ranging from 3.53 to 3.90 GHz and 3.56 to 3.91 GHz fully overlapping across all polarization states for the simulated and measured results, respectively. Experimental results affirm the robust performance of the proposed ADRA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
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".