  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.
