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Stochastic Power Consumption Model of Wireless Transceivers.

Paweł Kryszkiewicz1, Adrian Kliks1, Łukasz Kułacz1

  • 1Institute of Radiocommunications, Poznan University of Technology, 61-131 Poznan, Poland.

Sensors (Basel, Switzerland)
|August 23, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces a novel stochastic energy consumption model for wireless transceivers. By treating model parameters as random variables, it enhances accuracy for network design and energy efficiency assessments.

Keywords:
hardware measurementspower consumptionsystem level simulationswireless transceivers

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Area of Science:

  • Electrical Engineering
  • Computer Science
  • Wireless Communications

Background:

  • Energy efficiency is critical for modern wireless networks and transceivers.
  • Existing energy consumption models are either device-specific or oversimplified for broad application.
  • Accurate modeling is needed to capture transceiver energy variability.

Purpose of the Study:

  • To propose a new stochastic energy consumption model for wireless transceivers.
  • To account for the variability in power consumption across different devices and vendors.
  • To enable more detailed system-level network design and analysis.

Main Methods:

  • Developed a fixed energy consumption model with parameters as random variables.
  • Calibrated model parameters for 14 individual WiFi modems.
  • Modeled parameter distributions, their characteristics, and correlations based on measured data.

Main Results:

  • Successfully modeled the variability of transceiver energy consumption using stochastic parameters.
  • Demonstrated the model's applicability in system-level network design.
  • Provided a more detailed energy consumption characterization for a multi-hop link simulation.

Conclusions:

  • The proposed stochastic model offers a more accurate and flexible approach to energy efficiency assessment in wireless networks.
  • This method allows leveraging transceiver variability as a design parameter.
  • It facilitates enhanced performance analysis and optimization of wireless systems.