Phased Arrays and MIMO: Wideband 5G End Fire Elements on Liquid Crystal Polymer for MIMO
Bibliographic record
Abstract
This paper presents a multiport antenna for mobile communications at a symposium on phased arrays, and consequently it has two parts. Firstly, we review the context of the phased array antenna as a general array and multi-element antennas (MEAs) which are prevalent in mobile communications. There is overlap between phased arrays and MEAs in terms of the basic array principle, but the design approaches and typical applications are different. These differences are reviewed to help fix ideas about the terminology. The second part presents a new array antenna for fifth generation (5G) mobile communications. Its elements are wideband designs for end-fire radiation from the edge of a metallic platform, or chassis. Each element comprises a pair of different sized dipoles in a parallel configuration in order to achieve a wideband impedance bandwidth. The conducting dipoles are supported by a dielectric, which is Liquid Crystal Polymer (LCP). This has relatively low dielectric losses at millimeter-wave frequencies, resulting in an antenna radiation efficiency of more than 90% across a 63 % relative bandwidth. The frequency is from 22.8 GHz to 44 GHz which covers the recently- released 5G bands at 24, 28 and 38 GHz. The elements sit on the edges of a rectangular chassis and are directive away from these edges. The end-fire gains are more than 6 dBi. The elements are well-spaced because the electrical size of the chassis is sufficiently large, meaning that the mutual coupling within the basic design is very low, but can be even further decreased using decoupling configurations.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".