Design of 60 GHz millimeter‐wave SIW antenna for 5G WLAN/WPAN applications
Bibliographic record
Abstract
Abstract Broadband millimeter Wave (mmWave) transmission at the 60 GHz band is a great prospect to meet the demanding high data rate requirements of future wireless personal area network (WPAN) and wireless local area network (WLAN) 5G networks. This paper proposes a single layer H‐plane sectoral horn mmWave antenna at 60 GHz using substrate integrated waveguide (SIW) technology for the future high‐speed short range WPAN and WLAN networks. The benefits of the proposed antenna are high gain, low cost, small size, and ease of integration with other planar circuits. The proposed SIW horn is constructed with RT/duroid 5880 substrate, which has a relative permittivity and loss tangent with a thickness of 0.508 mm. The novelty of this work is; a wider bandwidth is achieved by adding striplines at the horn aperture to match the antenna with air and to increase the antenna operating bandwidth. In addition, the antenna gain is improved by adding a dielectric lens with the striplines at the radiating end. During these steps, the antenna parameters are tuned and optimized to achieve the best results as compared to related previous studies. The proposed antenna's performance is analyzed in terms of gain, return loss (S11) and radiation pattern at a frequency of 60 GHz. Simulation results are carried out by using industry standard software, Computer Simulation Technology (CST) microwave studio. The designed antenna achieves a peak gain of 13 dB and impedance bandwidth when , 8.6 GHz (13.688%) for the reflection coefficient of . The results show that the proposed antenna achieves stable tunable 60 GHz frequency performance, which makes it feasible to deploy in WLAN/WPAN operating in mmWave bands.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".