Simulation and optimization of rectenna systems
Bibliographic record
Abstract
In this paper, we present an entirely simulation-based method to predict the performance of a complete rectenna system that includes all its components: the receiving antenna, the matching circuits between the antenna and the rectification circuit, and the load circuit. Whereas previous efforts to predict the performance of a rectenna system subdivided the system into the antenna part (radiation to AC power conversion) and the circuit part (AC power to DC power conversion), and made assumptions about the performance of the non-linear part of the rectenna based on a specified power level and frequency, in this method, the radiation part of the system is incorporated into the simulation by using Thevenin theorem. The method proposed in this work enables the rectenna designer to predict the performance of the complete rectenna system, at the design stage, for variation in the incident field's power density, angle of incidence, and operating frequency. Such performance prediction was not available before. Furthermore, the proposed method enables the rectenna designers to optimize the entire system over a portion of or the entire range of the operating frequency. Experimental results are provided to demonstrate the accuracy of the method.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 0.000 |
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 teacher head, 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".