Compact QMSIW Self-Diplexing MIMO Antenna
Bibliographic record
Abstract
In this letter, a dual-band, four-port multiple-input–multiple-output (MIMO) self-diplexing antenna is designed based on quarter-mode substrate integrated waveguide (QMSIW) resonators. The MIMO antenna configuration includes identical self-diplexing resonators arranged in a mirrored manner. The proposed antenna operates at 3.5 GHz (when Ports-1 and -2 are active) and 4.9 GHz (when Ports-3 and -4 are active), occupying a compact area of 0.25$\lambda _{g}^{2}$($\lambda _{g}$is calculated at 3.5 GHz). A full-mode substrate integrated waveguide (SIW) structure is initially designed and then modified into an asymmetric QMSIW configuration. Capacitive slots with different effective capacitances are added to enable operation at two distinct frequencies. Compactness is achieved through the use of QMSIW resonators instead of full-mode SIW resonators and the integration of capacitive slots within each QMSIW resonator. The antenna exhibits low mutual coupling ($-$22.89 dB) due to sufficient spacing between the resonators. The antenna gains are found to be 4.38 dBi at 3.5 GHz and 5.98 dBi at 4.9 GHz. The MIMO channel parameters, such as envelope correlation coefficient and diversity gain, are also evaluated and found to be satisfactory. The antenna’s attractive features, compact size, low mutual coupling, independent frequency control, and excellent MIMO channel performance, make it well suited for compact radio frequency devices. To the best of the authors’ knowledge, this is the most compact MIMO self-diplexing antenna reported to date.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 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".