  Federated Learning (FL) has been recently presented as a new technique for
training shared machine learning models in a distributed manner while
respecting data privacy. However, implementing FL in wireless networks may
significantly reduce the lifetime of energy-constrained mobile devices due to
their involvement in the construction of the shared learning models. To handle
this issue, we propose a novel approach at the physical layer based on the
application of lightwave power transfer in the FL-based wireless network and a
resource allocation scheme to manage the network's power efficiency. Hence, we
formulate the corresponding optimization problem and then propose a method to
obtain the optimal solution. Numerical results reveal that, the proposed scheme
can provide sufficient energy to a mobile device for performing FL tasks
without using any power from its own battery. Hence, the proposed approach can
support the FL-based wireless network to overcome the issue of limited energy
in mobile devices.
