Efficient Dual-band Ultra-Low-Power RF Energy Harvesting Front-End for Wearable Devices
Bibliographic record
Abstract
This paper presents a novel dual-band ultra-low power RF energy harvesting front-end for wearable devices, wireless sensor networks, and the Internet of things (IoT) designed in standard 130 nm CMOS technology. The proposed dual-band RF energy harvester operates at ISM bands of 915 MHz and 1.85 GHz and uses an efficient summation network to combine power from different frequency bands. A dual-band antenna receives signals from two different bands which are boosted by two different matching networks. Then, two self-compensated cross-coupled rectifiers convert the RF signals provided by the two different bands into DC output voltages. At the output of the two rectifiers, a summation network using switches and a control circuit combines power from different bands, charging the output capacitor. The post-layout simulation results demonstrate a sensitivity of -33 dBm for 1 V output at a capacitive load and the peak end-to-end efficiency is 43.2% at -18 dBm when two frequency bands are available. When only 915 MHz or 1.85 GHz is available, the results demonstrate a high peak efficiency of 42.3% and 44% at -16 dBm and -17 dBm, respectively..
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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 | 0.000 | 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 | 0.000 | 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".