A novel compact four-port MIMO dielectric resonator antenna with wideband operation for 5G mm-wave applications
Bibliographic record
Abstract
Abstract This work presents a compact wideband four-port Multiple-Input Multiple-Output (MIMO) Dielectric Resonator Antenna (DRA) for 5G applications in the millimeter-wave (mm-wave) band. The proposed MIMO structure comprises of four hexagonal dielectric resonator antennas (DRAs) mounted on a ground plane supported by a substrate, utilizing aperture-coupled microstrip feeding for excitation. Notches are incorporated at the center of the DRAs, enabling the excitation of multiple-resonant modes for achieving a wide bandwidth. Mutual coupling is reduced by employing a combination of isolation techniques, including polarization diversity, a defected ground structure (DGS), and metallic strips placed along the DRA sidewalls. The antenna operates over frequency band ranging between 22.99–30.49 GHz (28%) with maximum isolation greater than 33 dB. The achieved peak gain and radiation efficiency are 8.53 and 94.4% respectively. The design maintains a compact overall size of 1.60 λ o × 1.60 λ o × 0.20 λ o. The design approach is presented, emphasizing the effectiveness of the implemented isolation techniques. A prototype is developed and tested, demonstrating results that closely align with the simulations. The proposed MIMO antenna exhibits wideband operation, high isolation, and compactness, making it a promising candidate for modern 5G mm-wave MIMO 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 | 0.001 |
| 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) | 0.001 | 0.002 |
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".