Integrated LTE and Millimeter-Wave 5G MIMO Antenna System for 4G/5G Wireless Terminals
Bibliographic record
Abstract
This work demonstrates an integrated multiple-input multiple-output (MIMO) antenna solution for Long Term Evolution (LTE) and Millimeter-Wave (mm-wave) 5G wireless communication services. The proposed structure is comprised of a two-element LTE MIMO antenna, and a four-element 5G MIMO configuration with rectangular and circular defects in the ground plane. For experimental validation, the proposed structure is fabricated on a Rogers RO4350B substrate with 0.76 mm thickness. The overall substrate dimensions are 75 mm × 110 mm. The proposed structure is capable of operating at 5.29-6.12 GHz (LTE 46 and 47 bands) and 26-29.5 GHz (5G mm-wave) frequency bands. Additionally, the measured peak gain of 5.13 and 9.53 dB is attained respectively for the microwave and mm-wave antennas. Furthermore, the analysis of the MIMO performance metrics demonstrates good characteristics, and excellent field correlation performance across the operating bands. Furthermore, the analysis of the Specific Absorption Rate (SAR) and Power Density (PD) at the lower frequency band (5.9 GHz) and PD only at mm-Wave frequency band (28 GHz) verifies that the proposed antenna system satisfies the international human safety standards. Therefore, the proposed integrated MIMO antenna configuration ascertains to be a potential contender for the forthcoming communication 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".