Robust Transmission Design for Federated Learning Through Over-the-Air Computation  

作　　者：Hamideh Zamanpour Abyaneh Saba Asaad Amir Masoud Rabiei 

机构地区：[1]School of Electrical and Computer Engineering,College of Engineering,University of Tehran,Tehran,Iran [2]Department of Electrical Engineering and Computer Science,York University,Canada

出　　处：《China Communications》2025年第3期65-75,共11页中国通信(英文版)

摘　　要：Over-the-air computation(AirComp)enables federated learning(FL)to rapidly aggregate local models at the central server using waveform superposition property of wireless channel.In this paper,a robust transmission scheme for an AirCompbased FL system with imperfect channel state information(CSI)is proposed.To model CSI uncertainty,an expectation-based error model is utilized.The main objective is to maximize the number of selected devices that meet mean-squared error(MSE)requirements for model broadcast and model aggregation.The problem is formulated as a combinatorial optimization problem and is solved in two steps.First,the priority order of devices is determined by a sparsity-inducing procedure.Then,a feasibility detection scheme is used to select the maximum number of devices to guarantee that the MSE requirements are met.An alternating optimization(AO)scheme is used to transform the resulting nonconvex problem into two convex subproblems.Numerical results illustrate the effectiveness and robustness of the proposed scheme.

关 键 词：federated learning imperfect CSI optimization over-the-air computing robust design 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程] TN92[自动化与计算机技术—控制科学与工程]