Resonant Cavity Antennas for 5G Communication Systems: A Review
Bibliographic record
Abstract
Resonant cavity antennas (RCAs) are suitable candidates to achieve high-directivity with a low-cost and easy fabrication process. The stable functionality of the RCAs over different frequency bands, as well as, their pattern reconfigurability make them an attractive antenna structure for the next generation wireless communication systems, i.e., fifth generation (5G). The variety of designs and analytical techniques regarding the main radiator and partially reflective surface (PRS) configurations allow dramatic progress and advances in the area of RCAs. Adding different functionalities in a single structure by using additional layers is another appealing feature of the RCA structures, which has opened the various fields of studies toward 5G applications. This paper reviews the recent advances on the RCAs along with the analytical methods, and various capabilities that make them suitable to be used in 5G communication systems. To discuss different capabilities of RCA structures, some applicable fields of studies are followed in different sections of this paper. To indicate different techniques in achieving various capabilities, some recent state-of-the-art designs are demonstrated and investigated. Since wideband high-gain antennas with different functionalities are highly required for the next generation of wireless communication, the main focus of this paper is to discuss primarily the antenna gain and bandwidth. Finally, a brief conclusion is drawn to have a quick overview of the content of this paper.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".