New Self-Isolated MIMO Antenna Array for 5G mm-Wave Applications
Bibliographic record
Abstract
In this paper, a simple novel technique to self-isolate multiple-input-multiple-output (MIMO) antenna array elements for mm-wave applications is proposed. MIMO antenna arrays with inter-element separation of 0.2 mm (0.023λ at 35 GHz) and measured high isolation (>50 dB) are presented. Several rigorously optimized slots of different shapes, positions, and dimensions are etched on the radiating patch to enhance the inter-element isolation within 28-37.5 GHz impedance bandwidth. The surface current distributions, parametric analysis, and two MIMO array configurations are employed to validate the proposed self-isolation technique. The novel mm-wave antenna exhibits high impedance bandwidth (>29%), high isolation (>50dB), high efficiency (>90%), high gain (>9.5 dB), and low envelope correlation coefficient (<0.005) throughout the desired bandwidth. Two configurations of the MIMO antenna arrays are fabricated and measured to validate the simulation outcomes. To the best of the authors’ knowledge, the presented design is the first to exhibit such wideband isolation improvement without any external decoupling structure at the mm-wave frequency range.
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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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".