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Rozproszone Wykrywanie Zajętości Widma Oparte na Uczeniu Federacyjnym

Łukasz Kułacz, Adrian Kliks

TL;DR

The paper discusses the results of the conducted hardware experiment, where FL has been applied for DVB-T signal detection, and presents a distributed federated learning approach that addresses this challenge for sensors without access to learning data.

Abstract

Spectrum occupancy detection is a key enabler for dynamic spectrum access, where machine learning algorithms are successfully utilized for detection improvement. However, the main challenge is limited access to labeled data about users transmission presence needed in supervised learning models. We present a distributed federated learning approach that addresses this challenge for sensors without access to learning data. The paper discusses the results of the conducted hardware experiment, where FL has been applied for DVB-T signal detection.

Rozproszone Wykrywanie Zajętości Widma Oparte na Uczeniu Federacyjnym

TL;DR

The paper discusses the results of the conducted hardware experiment, where FL has been applied for DVB-T signal detection, and presents a distributed federated learning approach that addresses this challenge for sensors without access to learning data.

Abstract

Spectrum occupancy detection is a key enabler for dynamic spectrum access, where machine learning algorithms are successfully utilized for detection improvement. However, the main challenge is limited access to labeled data about users transmission presence needed in supervised learning models. We present a distributed federated learning approach that addresses this challenge for sensors without access to learning data. The paper discusses the results of the conducted hardware experiment, where FL has been applied for DVB-T signal detection.

Paper Structure

This paper contains 8 sections, 9 figures.

Figures (9)

  • Figure 1: Topologia sieci używana podczas pomiarów.
  • Figure 2: Prawdopodobieństwo detekcji (współczynnik IDW=0)
  • Figure 3: Prawdopodobieństwo detekcji (współczynnik IDW=1)
  • Figure 4: Prawdopodobieństwo detekcji (współczynnik IDW=2)
  • Figure 5: Prawdopodobieństwo detekcji (współczynnik IDW=3)
  • ...and 4 more figures