Compute-Update Federated Learning: A Lattice Coding Approach

IF 4.6 2区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Seyed Mohammad Azimi-Abarghouyi;Lav R. Varshney
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引用次数: 0

Abstract

This paper introduces a federated learning framework that enables over-the-air computation via digital communications, using a new joint source-channel coding scheme. Without relying on channel state information at devices, this scheme employs lattice codes to both quantize model parameters and exploit interference from the devices. We propose a novel receiver structure at the server, designed to reliably decode an integer combination of the quantized model parameters as a lattice point for the purpose of aggregation. We present a mathematical approach to derive a convergence bound for the proposed scheme and offer design remarks. In this context, we suggest an aggregation metric and a corresponding algorithm to determine effective integer coefficients for the aggregation in each communication round. Our results illustrate that, regardless of channel dynamics and data heterogeneity, our scheme consistently delivers superior learning accuracy across various parameters and markedly surpasses other over-the-air methodologies.
计算-更新联合学习:网格编码方法
本文介绍了一种联合学习框架,该框架利用新的源信道联合编码方案,通过数字通信实现空中计算。该方案不依赖设备上的信道状态信息,而是采用晶格编码对模型参数进行量化,并利用来自设备的干扰。我们提出了一种新颖的服务器接收器结构,旨在可靠地解码量化模型参数的整数组合,将其作为用于聚合的网格点。我们提出了一种数学方法来推导所提方案的收敛边界,并提供了设计说明。在此背景下,我们提出了一种聚合指标和相应的算法,以确定每轮通信中聚合的有效整数系数。我们的结果表明,无论信道动态和数据异构性如何,我们的方案都能在各种参数下始终提供卓越的学习准确性,并明显优于其他空中方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing 工程技术-工程:电子与电气
CiteScore
11.20
自引率
9.30%
发文量
310
审稿时长
3.0 months
期刊介绍: The IEEE Transactions on Signal Processing covers novel theory, algorithms, performance analyses and applications of techniques for the processing, understanding, learning, retrieval, mining, and extraction of information from signals. The term “signal” includes, among others, audio, video, speech, image, communication, geophysical, sonar, radar, medical and musical signals. Examples of topics of interest include, but are not limited to, information processing and the theory and application of filtering, coding, transmitting, estimating, detecting, analyzing, recognizing, synthesizing, recording, and reproducing signals.
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