Fixed-Beam Frequency-Tunable Phase-Reversal Coplanar Stripline Antenna Array
Bibliographic record
Abstract
A fixed-beam frequency-tunable coplanar stripline (CPS) antenna array using the phase reversal technique and varactor diodes tuning is presented. The antenna array is composed of plurality of half-wavelength CPS sections interconnected by phase reversing crossovers. These crossovers have two functions: they serve as the radiators (small dipoles) of the array and also provide their own required in-phase excitations for broadside radiation. Two microstrip-to-CPS transitions for excitation of the balanced input/output antenna array are implemented and compared. A six-element array is demonstrated theoretically and experimentally, with 9.3 dBi of gain for bidirectional radiation and 12.5 dBi of gain for unidirectional radiation using a back reflector. Moreover, shunt varactor diodes are incorporated along the CPS structure to achieve frequency tuning through a bias voltage control while broadside radiation patterns remain fixed. The return loss and the radiation patterns at several frequencies are presented, and up to 50% tuning range is obtained. The proposed antenna array is simple and uniplanar with small lateral size, high radiation efficiency and high directivity. In addition, it uses a very simple biasing circuit with high DC-RF isolation. Its balanced input/output makes it suitable for RF system integration and active integrated antenna design.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".