Random Aggregate Beamforming for Over-the-Air Federated Learning in Large-Scale Networks

arXiv:2403.18946v1 Announce Type: cross
Abstract: At present, there is a trend to deploy ubiquitous artificial intelligence (AI) applications at the edge of the network. As a promising framework that enables secure edge intelligence, federated learning (FL) has received widespread attention, and over-the-air computing (AirComp) has been integrated to further improve the communication efficiency. In this paper, we consider a joint device selection and aggregate beamforming design with the objectives of minimizing the aggregate error and maximizing the number of selected …

abstract applications artificial artificial intelligence arxiv attention computing cs.ai cs.it cs.lg deploy edge edge intelligence federated learning framework intelligence math.it network networks random scale the edge trend type