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Federated Learning-Based Spectrum Occupancy Detection.

Łukasz Kułacz1, Adrian Kliks1,2

  • 1Institute of Radiocommunications, Poznan University of Technology, 60-965 Poznan, Poland.

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Summary
This summary is machine-generated.

This study introduces a federated learning algorithm for distributed spectrum occupancy detection, enhancing radiocommunication efficiency. The method improves accuracy and data exchange, even with faulty sensors.

Keywords:
federated learningmachine learningspectrum occupancy detection

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Area of Science:

  • Electrical Engineering
  • Computer Science
  • Signal Processing

Background:

  • Dynamic spectrum access is crucial for efficient radiocommunication due to limited spectrum resources.
  • Effective spectrum occupancy detection is a key challenge in dynamic spectrum access systems.
  • Machine learning algorithms can enhance spectrum detection effectiveness.

Purpose of the Study:

  • To present a federated learning algorithm for distributed spectrum occupancy detection.
  • To improve the overall effectiveness of spectrum detection while minimizing data exchange between sensors.
  • To evaluate the proposed algorithm's performance against traditional methods and its resilience to faulty sensors.

Main Methods:

  • Development of a federated learning algorithm tailored for distributed spectrum occupancy detection.
  • Implementation of the algorithm using actual radio signal samples collected in a laboratory setting.
  • Comparative analysis of the federated learning approach against separate, autonomous models.

Main Results:

  • The proposed federated learning algorithm achieves higher accuracy in spectrum occupancy detection compared to non-federated models.
  • The solution effectively reduces the amount of data exchanged between sensors.
  • The algorithm demonstrates robustness and resistance to faulty sensors within the system.

Conclusions:

  • Federated learning offers an effective approach for distributed spectrum occupancy detection in radiocommunication.
  • The proposed algorithm enhances detection accuracy and minimizes data transmission, making it suitable for sensor networks.
  • The solution is particularly valuable in environments with unreliable or faulty sensor nodes.