Octagonal Patch Antenna with Modified SRR Width and Ground Slot for Sub-6 GHz Band
Bibliographic record
Abstract
This paper presents a miniaturized patch antenna that integrates an octagonal split-ring resonator (SRR) and a square-slot defected ground structure (DGS) for sub-6 GHz wireless applications. Designed on an FR-4 substrate ($\varepsilon_{r}=$ 4.3, thickness $\boldsymbol{=} \mathbf{1 . 6 ~ m m}$), the antenna achieves a compact $10 \times 10 \times 1.6 \mathbf{~ m m}^{3}$ footprint, which is significantly smaller than conventional patch designs. The optimized configuration operates across $\mathbf{4 . 2 0 - 7 . 0 5 ~ G H z}$, covering upper sub-6 GHz 5G New Radio (NR), Wi-Fi 6/6E, and IoT frequency bands. The SRR enhances electromagnetic coupling, while the DGS improves impedance matching and bandwidth by suppressing unwanted resonances. Simulations indicate a return loss of −31 dB at 5.9 GHz, a wide impedance bandwidth of 2.85 GHz, and a peak gain of −2.8 dBi. Although the gain is modest compared with larger antennas, it is sufficient for short-range IoT gateways, smart sensors, and compact 5G devices, where small form factor and wideband compliance is more critical than high directive gain. The results demonstrate that SRR- and DGS-based techniques provide an effective approach for antenna miniaturization and wideband operation, offering a promising solution for next-generation compact wireless 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) | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".