Research Area: Machine Learning
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.
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Author(s) Name: Ha-Vu Tran; Georges Kaddoum; Hany Elgala; Chadi Abou-Rjeily; Hemani Kaushal
Journal name: IEEE Communications Letters
Conferrence name:
Publisher name: IEEE
DOI: 10.1109/LCOMM.2020.2985698
Volume Information: ( Volume: 24, Issue: 7, July 2020) Page(s): 1472 - 1476
