Joint Tx Power Allocation and Rx Power Splitting for SWIPT System With Multiple Nonlinear Energy Harvesting Circuits
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Bibliographic record
Abstract
We study the joint transmit (Tx) power allocation and receive (Rx) power splitting for simultaneous wireless information and power transfer (SWIPT). Considering the practical scenario of nonlinear energy harvesting (EH), we adopt the realistic nonlinear EH model for analysis. To address the critical nonlinearity issue due to the saturation, we propose using multiple EH circuits in parallel. An important problem is to maximize the achievable rate by jointly optimizing Tx power allocation and Rx power splitting, which is a nonconvex problem. In this letter, we first derive the optimal solution for any number of EH circuits. Then, we study how the number of EH circuits required to avoid the saturation should be determined. From the obtained results, we draw useful and interesting insights into the SWIPT system with nonlinear EH. Numerical results demonstrate that employing multiple EH circuits substantially enhances the SWIPT performance with nonlinear EH.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it