Side-Lobe Level Reduction of Half-Mode Substrate Integrated Waveguide Leaky-Wave Antenna
Bibliographic record
Abstract
In this communication, we introduce a novel design for mitigating the side-lobe level (SLL) of the half-mode substrate integrated waveguide (HMSIW)-based leaky-wave antenna (LWA). Applying a novel approach through modification of the side aperture of HMSIW, we achieved an SLL of -13.8 and -11.2 dB in the upper hemisphere and full space, respectively. The key novelty of this communication is the reduction of SLL in full space while the state-of-the-art antennas only mitigated the SLL in the upper hemisphere. Furthermore, tapering the open side aperture in a thin trapezoid shape led to a significant reduction of beam squint. The operating frequency band of the antenna matches the allocated 5G wireless network millimeter-wave bands from 26 to 30 GHz. The measured peak realized gain of the antenna is 10.6 dBi at 28.5 GHz. The length, width, and height of the HMSIW antenna are 70, 15, and 0.5 mm, respectively. The antenna was fabricated on a Rogers RT/Duroid 5880 substrate. Excellent agreement between the measurements and simulated results was observed. The discrepancies between the measured and simulated results were analyzed by a complete and thorough sensitivity analysis that included the effects of the fabrication tolerances, connectors' misalignment, and bending due to the mechanical stress. High gain, low SLL, and compactness are among the advantages of the proposed antenna making it a suitable candidate for the miniaturization of 5G communication systems.
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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) | 0.000 | 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".