A quad port MIMO antenna with improved bandwidth and high gain for 38 GHz 5G applications
Bibliographic record
Abstract
With this paper, a novel 2 × 2 Multiple Input Multiple Output (MIMO) antenna for forthcoming 5G applications is introduced. The design of the MIMO antenna comprises of four modified rectangular patches and a perforated ground plane, achieved through circular and rectangular patterns, to meet the desired objectives. The antenna is constructed on Roger RT/duroid 5880 substrate, with physical measurements 35×30×0.8mm3 and a dielectric constant of 2.2. The proposed antenna has undergone simulation and analysis utilizing both the High-Frequency Structure Simulator (HFSS) and Computer Simulation Technology (CST) in order to confirm its utility. The antenna has a wide spectrum of 8.9 GHz resonating from 34.8 to 43.7 GHz. The suggested antenna has a peak gain of approximately 10.24 dBi at 38.70 GHz. Additionally; it has an isolation below -20 dB. The MIMO antenna that has been simulated exhibits strong diversity characteristics, including a low envelope correlation coefficient (ECC < 0.0002), minimal channel capacity loss (CCL < 0.4), a significant reduction in total active reflection coefficient (TARC < -8dB), and a substantial diversity gain (DG > 9.999). The suggested MIMO antenna covers the n260 band (37-40 GHz) and the n259 band (39.5- 43.5), which is widely used in different countries, such as the USA, Canada, Korea and Australia. All these findings and the small size demonstrate the capabilities of the designed antenna for future 5G applications.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".