# Por'ownanie metod detekcji zajketo'sci widma radiowego z wykorzystaniem uczenia federacyjnego z oraz bez wkezla centralnego

arXiv: https://arxiv.org/abs/2304.04754 · HTML: https://mlsanity.com/paper/2304.04754/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 0 of its 9 references that are in the map.
- First posted on arXiv 31 Mar 2023.

## Abstract (arXiv)

Dynamic spectrum access systems typically require information about the spectrum occupancy and thus the presence of other users in order to make a spectrum al-location decision for a new device. Simple methods of spectrum occupancy detection are often far from reliable, hence spectrum occupancy detection algorithms supported by machine learning or artificial intelligence are often and successfully used. To protect the privacy of user data and to reduce the amount of control data, an interesting approach is to use federated machine learning. This paper compares two approaches to system design using federated machine learning: with and without a central node.