Analysis and Impact of Port Impedances on Two-Port Networks and Its Application in Active Array Antenna Developments
Bibliographic record
Abstract
In this work, we present a comprehensive analysis of port impedance effects on a signal coupled across two-port networks, derive an equation to evaluate the impedances for a specified coupling, and demonstrate two beam-shaping active array antenna prototypes to validate the theory. In this context, the generalized S-parameters are theoretically studied and verified through an example. Subsequently, a closed-form equation is derived to accurately evaluate the port impedances that enable the achievement of a desired magnitude and phase of the signal coupling across the two-port network. The meaningfulness of all the potential results and the additional capabilities of derived equations are then discussed. With this understanding, a general modeling procedure is formulated to achieve the simultaneous amplification and phase shifting only through the active devices, without resorting to any additional passive circuitry. As a proof of concept, two 1 ×5 active array antenna prototypes are developed and fabricated at 5 GHz: one for broadside radiation with a sidelobe level of less than -20 dB requirement, and the other for flat-top radiation beam between -10° and 30°. They are integrated with a 1 ×5 Wilkinson power divider that is designed for radiation pattern measurements, and the corresponding results agree reasonably well with the simulated counterparts and theory, thereby proving the developed concept. Such solutions demonstrate the inherent advantages of being low-loss, compact, and efficient, which are essential for the next generation of 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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".