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Apr, 2024
基于自编码器的无线联邦学习中的AirComp星座设计
An Autoencoder-Based Constellation Design for AirComp in Wireless Federated Learning
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Yujia Mu, Xizixiang Wei, Cong Shen
TL;DR
该研究提出了一种支持数字调制的端到端通信系统,旨在克服数字调制的AirComp中精确解码总和信号的挑战,通过使用自编码器网络结构和发射机、接收机组件的共同优化,填补了数字调制的AirComp情景中精确解码总和信号的重要空白,可以推动联邦学习在当代无线系统中的部署。
Abstract
wireless federated learning
(FL) relies on efficient uplink communications to aggregate model updates across distributed edge devices.
over-the-air computation
(a.k.a. AirComp) has emerged as a promising approach
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