Modeling and simulation of an antenna with optimized AMC reflecting layer for gain and front-to-back ratio enhancement for 5G applications
Bibliographic record
Abstract
Abstract A low-profiled microstrip patch antenna for application in the 5G wireless communication systems is backed by a reflecting layer based on an optimized artificial magnetic conductor (AMC) to enhance the gain and the front-to-back ratio. The design and analyses process were carried out using the full-wave commercial simulator CST Microwave Studio in parallel with Matlab, using the embedded CST to Matlab VBA-based interface to create an automated simulation environment and to design both a conventional antenna and the proposed one. A genetic algorithm (GA) is used to optimize the AMC reflecting layer to achieve maximum gain and front-to-back ratio around the frequency band of interest. The results yield an important enhancement in the peak gain and front-to-back ratio, alongside a low side-lobe level (SLL) due to the successful surface waves suppression, thus making this antenna design a good candidate for future wireless communication systems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".