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Chapter

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Title

Spectrum Occupancy Detection Supported by Federated Learning

Authors

[ 1 ] Instytut Radiokomunikacji, Wydział Informatyki i Telekomunikacji, Politechnika Poznańska | [ P ] employee

Scientific discipline (Law 2.0)

[2.3] Information and communication technology

Year of publication

2023

Chapter type

chapter in monograph / paper

Publication language

english

Keywords
EN
  • federated learning
  • machine learning
  • spectrum occupancy detection
Abstract

EN Dynamic spectrum access is essential for radiocommunication and its limited spectrum resources. The key element of dynamic spectrum access systems is effective spectrum occupancy detection. In many cases, machine learning algorithms improve detection effectiveness. Because of the recent trend of using federated learning, a federated learning algorithm is presented in the context of distributed spectrum occupancy detection. The results of the work presented in the paper are based on actual signal samples collected in the laboratory. The proposed algorithm is effective, especially in the context of a set of sensors with faulty sensors.

Pages (from - to)

1 - 3

DOI

10.23919/SoftCOM58365.2023.10271668

URL

https://ieeexplore.ieee.org/document/10271668

Book

2023 31st International Conference on Software, Telecommunications and Computer Networks - SoftCOM 2023

Presented on

31st International Conference on Software, Telecommunications and Computer Networks, SoftCOM 2023, 21-23.09.2023, Split, Croatia

Ministry points / chapter

20

Ministry points / conference (CORE)

20

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