Ultra-Wideband Antenna Array for Modern Millimeter-Wave Wireless Applications
Bibliographic record
Abstract
An ultra-wideband antenna with high gain performance for future 5G and beyond millimeter-wave (mm-wave) applications is presented in this paper. The proposed microstrip patch antenna element was designed based on an aperture-coupled microstrip patch with four loaded parasitic patches to improve the frequency bandwidth. The antenna was built by employing four metal layers. Roger RT/duroid 6006 and RT/duroid 6002 were used in this design as feeding and antenna substrates, respectively. The suggested antenna element was utilized to construct a 2×2 antenna array fed with a corporate feeding network to achieve high gain and desired radiation characteristics. ANSYSEDT 2022 R1 full-wave simulator was used to design and analyze the proposed antenna and the corporate feeding network. The array gain is between 9.5 dB and 13.2 dB over the desired band of interest. The attained reflection coefficient (S11) of better than -10 dB is in the range of 26.15 GHz – 38.6 GHz, occupying a relatively compact antenna size. Moreover, the presented antenna realizes a low cross-polarization and a good front-to-back ratio. The obtained results show that the presented antenna can be considered an excellent candidate for modern wireless communication systems in mm-wave wideband 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 | 0.000 | 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".