Reconfigurable Antennas for RF Energy Harvesting Application: Current Trends, Challenges, and Solutions from Design Perspective
Bibliographic record
Abstract
Due to the widespread use of low-power embedded devices in both industrial and consumer applications, research into the use of alternate energy sources has been sparked by the requirement for continuous power. Due to its accessibility and ability to be implanted, RF energy is always taken into consideration among the traditional energy sources that are currently available. There is a significant necessity for efficient RF front-ends, which must provide effective circular polarization (CP) features, effectiveness, feasibility from a design standpoint, and optimal usage of ambient RF signals accessible in the environment. So, for understanding their utilization in RF energy harvesting, a metasurface reflector-inspired CP-printed reconfigurable antenna integrated with a Greinacher voltage divider (GVD) rectifier circuit is reported. It offers broadband CP with fractional bandwidth > 25%, CP gain > 8.35 dBic, and directional radiation with the 3 dB angular beamwidth > 100° in the 3.5/5 GHz bands. With the integration of the rectifier circuit, a theoretical DC output > 4.8 V at 12 dBm is obtained. The acceptable impedance bandwidth, axial ratio bandwidth, antenna gain, antenna efficiency, and directional radiation with a 3 dB angular beamwidth value are studied and subsequently matched with the trade-offs (usage of diodes, complexity of DC biasing circuits, and attainment of polarization reconfigurability) obtained from the state of the art. A comprehensive study of the reconfigurable antennas is reported to highlight the findings as a widespread solution for these limitations in RF energy harvesting application.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".