Enhanced Isolation in CDRA Massive MIMO Arrays Using Alternating Slot Orientation Rotation (ASOR)
Bibliographic record
Abstract
This paper presents a compact and efficient Circular Dielectric Resonator Antenna (CDRA) array design formassive MIMO base stations operating at 5.8 GHz. The proposed array utilizes a novel technique named ASOR (Alternating Slot Orientation Rotation), in which the orientation of the slot-feed is alternated between adjacent elements to achieve polarization diversity and reduce mutual coupling. The array performance is validated through full-wave simulations using CST Studio Suite. The simulated results demonstrate excellent impedance matching with reflection coefficients (|S11|) below –10 dB and strong inter-element isolation (|S21| < –20 dB) across the operating band, without the need for additional decoupling structures. The far-field radiation pattern shows stable directional gain with a main lobe magnitude of 5.62 dBi and a 3 dB beamwidth of 74°, while maintaining low side lobe levels. The gain remains stable near 6.9 dBi at 5.8 GHz. Moreover, the envelope correlation coefficient (ECC) at the operating frequency is reduced to below 10⁻⁶ after applying ASOR, ensuring excellent diversity performance. The proposed approach offers a simple yet effective solution for mutual coupling suppression, enabling high-efficiency, scalable, and practical antenna arrays for next-generation massive 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) | 0.000 | 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".