Ten Antenna Array Using a Small Footprint Capacitive-Coupled-Shorted Loop Antenna for 3.5 GHz 5G Smartphone Applications
Bibliographic record
Abstract
A self-isolated 10-element antenna array operating in the long-term evolution 42 (LTE42) frequency band is proposed for 5G massive MIMO smartphone applications. The proposed antenna elements are placed in a 2D array configuration; they are placed symmetrically along the two long edges of the mobile chassis. The proposed antenna structure is a shorted loop antenna resonating at half-wavelength mode, which is rarely deployed by researchers due to its large size compared to other quarter wavelength antenna structures. It is a printed, shorted, and compact loop antenna of a total footprint area of 6 × 6.5 mm2 (λ/14.3 ×λ/13.2, where λ is the free space wavelength at 3.5 GHz). A small capacitive coupling flag-shaped strip is used to excite the proposed loop antenna. The compactness is achieved using an inward meandering that forms an internal loop in the element. The position and the dimensions of this loop are used to tune the resonant frequency and matching level at 3.5 GHz. The results (theoretical, simulated, and measured) show that the 3.5 GHz band (3.4-3.6 GHz) is achieved with impedance matching better than -10 dB, and total efficiency higher than 65%. A 10 × 10 MIMO system is formed and it has an excellent MIMO and diversity performance in-terms of the envelope correlation coefficient (below 0.055), and apparently it has the highest channel capacity (about 54.3 bps/Hz) among other MIMO systems of the same order. Simulation results of the specific absorption rate (SAR) demonstrates that the proposed antenna solution satisfied SAR criterion. Thus, the proposed ten-element MIMO antenna represent an excellent candidate for sub-6 GHz 5G smartphone 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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".