Rectifier Efficiency Model Validation for RFID Wireless Power Transfer

5.5 KB of simulation results validating a joint power-time optimization framework for 915 MHz RFID-based wireless power transfer systems. The dataset, authored by Lina Yuan and last updated in May 2026, likely contains metrics comparing the proposed Model Predictive Control and ADMM-based algorithm against conventional PID controllers. Results described in the associated paper demonstrate a 37.6% peak efficiency and 61.9% reduction in power fluctuations for IoT tags over 0.5–5 meter distances.

Use Cases

• Benchmarking wireless power transfer efficiency models based on the described Friis path loss and rectifier non-linearity models.
• Validating adaptive power control algorithms for time-varying channels based on the Model Predictive Control mechanism.
• Analyzing fairness in energy allocation among multiple IoT sensors based on the described TDMA slot optimization framework.
• Comparing distributed optimization techniques like ADMM against centralized methods for non-convex joint resource allocation problems.

Strengths

• Includes specific performance metrics: 37.6% peak efficiency and 61.9% reduction in power fluctuations.
• Models detailed system components: 5-stage Dickson rectifier non-linearity and storage capacitor dynamics.
• Validated for heterogeneous IoT loads (temperature, IMU, vision sensors) over a defined 0.5–5 m operational range.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is very small (5.5 KB), indicating limited scope, likely containing summary results rather than raw simulation data.

Provenance

Source

Lina Yuan via figshare

Collection Method

Likely generated from simulations described in the associated research paper.

Time Range

Simulation timeframe not specified.

Freshness

Last updated 2026-05-04 17:25:14; freshness should be verified.

Geography

Not applicable; simulation-based.