Dual-band millimetre wave MIMO antenna with reduced mutual coupling based on optimized parasitic structure and ground modification
Bibliographic record
Abstract
In this study, a high-isolation dual-band (28/38 GHz) multiple-input-multiple-output (MIMO) antenna for 5G millimeter-wave indoor applications is presented. The antenna consists of two interconnected patches. The primary patch is connected to the inset feed, while the secondary patch is arc-shaped and positioned over the main patch, opposite to the feed. Both patches function in the lower 28 GHz band, while the primary patch is accountable for inducing the upper 38 GHz band. An expedited trust-region (TR) algorithm is employed to optimize the dimensions of the antenna components, ensuring the antenna operates efficiently with high reflection at both bands. The antenna demonstrates a gain exceeding 7 dBi at both frequencies. An array of four antennas is configured orthogonally to create a MIMO system with isolation surpassing 19 dB. The isolation is further enhanced through the addition of a circular parasitic patch at the front and modifications made to the ground. The TR method is employed again to optimize their parameters and achieve the desired isolation, exceeding 32 dB at both bands. The MIMO system demonstrates outstanding diversity performance at both frequencies, characterized by low values of the envelope correlation coefficient (ECC) (< 10 - 4), channel capacity loss (CCL) (< 0.03 bit/s/Hz), and total active reflection coefficient (TARC) (< - 10 dB). Additionally, it secures a diversity gain (DG) exceeding 9.99 dB. The MIMO system is manufactured and tested, showing good alignment between simulation and measurement data for all performance metrics.
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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 | 0.000 | 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".