A New Method to Design a Rectifying Antenna for Ambient RF Energy Harvesting
Bibliographic record
Abstract
Due to their ever-increasing energy density, Rectifying Antennas (Rectenna) are increasingly being used as a power source for ultra-low-consumption electronic devices. However, most designers only define the optimal features of the rectenna, which does not account for performance in real-life situations. In this paper, an analysis of the real-time performance of the main characteristics of a rectenna (the DC output voltage and conversion efficiency) is proposed. Ambient power density measurements at 2.4 GHz are made, and based on observations, an optimized rectenna in the 2.45 GHz band is designed for voltage and efficiency characterization. The designed rectenna demonstrates an optimal conversion efficiency of 47.4% and a DC voltage of 0.46 V, for an input power of -4 dBm. Analysis of the performance of the rectenna according to the ambient data allows observing over 17 minutes, the average efficiency of 28%, and an average voltage of 0.14 V.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".