  Federated learning (FL) is an emerging technique aiming at improving
communication efficiency in distributed networks, where many clients often
request to transmit their calculated parameters to an FL server simultaneously.
However, in wireless networks, the above mechanism may lead to prolonged
transmission time due to unreliable wireless transmission and limited
bandwidth. This paper proposes a communication scheme to minimize the uplink
transmission time for FL in wireless networks. The proposed approach consists
of two major elements, namely a modified Ring All-reduce (MRAR) architecture
that integrates D2D wireless communications to facilitate the communication
process in FL, and a modified Ant Colony Optimization algorithm to identify the
optimal composition of the MRAR architecture. Numerical results show that our
proposed approach is robust and can significantly reduce the transmission time
compared to the conventional star topology. Notably, the reduction in uplink
transmission time compared to baseline policies can be substantial in scenarios
applicable to large-scale FL, where client devices are densely distributed.
