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- Publisher Website: 10.1109/GLOBECOM42002.2020.9322334
- Scopus: eid_2-s2.0-85100391477
- WOS: WOS:000668970501125
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Conference Paper: One-Bit Over-the-Air Aggregation for Communication-Efficient Federated Edge Learning
Title | One-Bit Over-the-Air Aggregation for Communication-Efficient Federated Edge Learning |
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Authors | |
Keywords | Convergence Wireless communication Signal to noise ratio Servers Computational modeling |
Issue Date | 2020 |
Publisher | Institute of Electrical and Electronics Engineers. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000308 |
Citation | Proceedings of GLOBECOM 2020 - 2020 IEEE Global Communications Conference, Virtual Conference, Taipei, Taiwan, 7-11 December 2020, p. 1-6 How to Cite? |
Abstract | To mitigate the multi-access latency in federated edge learning, an efficient broadband analog transmission scheme has been recently proposed, featuring the aggregation of analog modulated gradients via the waveform-superposition property of the wireless medium. However, the assumed linear analog modulation makes it difficult to deploy this technique in modern wireless systems that exclusively use digital modulation. To address this issue, we propose in this work a novel digital version of broadband over-the-air aggregation, called one-bit broadband digital aggregation. The new scheme features one-bit gradient quantization followed by digital modulation at the edge devices and a simple threshold-based decoding at the edge server. We develop a comprehensive analysis framework for quantifying the effects of wireless channel hostilities (channel noise and fading) on the convergence rate. The analysis shows that the hostilities slow down the convergence of the learning process by introducing a scaling factor and a bias term into the gradient norm. However, all the negative effects vanish as the number of devices grows, but at a different rate for each type of channel hostility. |
Persistent Identifier | http://hdl.handle.net/10722/295915 |
ISSN | |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Zhu, G. | - |
dc.contributor.author | Du, Y | - |
dc.contributor.author | Gunduz, D | - |
dc.contributor.author | Huang, K | - |
dc.date.accessioned | 2021-02-08T08:15:50Z | - |
dc.date.available | 2021-02-08T08:15:50Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | Proceedings of GLOBECOM 2020 - 2020 IEEE Global Communications Conference, Virtual Conference, Taipei, Taiwan, 7-11 December 2020, p. 1-6 | - |
dc.identifier.issn | 2334-0983 | - |
dc.identifier.uri | http://hdl.handle.net/10722/295915 | - |
dc.description.abstract | To mitigate the multi-access latency in federated edge learning, an efficient broadband analog transmission scheme has been recently proposed, featuring the aggregation of analog modulated gradients via the waveform-superposition property of the wireless medium. However, the assumed linear analog modulation makes it difficult to deploy this technique in modern wireless systems that exclusively use digital modulation. To address this issue, we propose in this work a novel digital version of broadband over-the-air aggregation, called one-bit broadband digital aggregation. The new scheme features one-bit gradient quantization followed by digital modulation at the edge devices and a simple threshold-based decoding at the edge server. We develop a comprehensive analysis framework for quantifying the effects of wireless channel hostilities (channel noise and fading) on the convergence rate. The analysis shows that the hostilities slow down the convergence of the learning process by introducing a scaling factor and a bias term into the gradient norm. However, all the negative effects vanish as the number of devices grows, but at a different rate for each type of channel hostility. | - |
dc.language | eng | - |
dc.publisher | Institute of Electrical and Electronics Engineers. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/conhome.jsp?punumber=1000308 | - |
dc.relation.ispartof | IEEE Global Communications Conference (GLOBECOM) | - |
dc.rights | IEEE Global Communications Conference (GLOBECOM). Copyright © Institute of Electrical and Electronics Engineers. | - |
dc.rights | ©2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | - |
dc.subject | Convergence | - |
dc.subject | Wireless communication | - |
dc.subject | Signal to noise ratio | - |
dc.subject | Servers | - |
dc.subject | Computational modeling | - |
dc.title | One-Bit Over-the-Air Aggregation for Communication-Efficient Federated Edge Learning | - |
dc.type | Conference_Paper | - |
dc.identifier.email | Huang, K: huangkb@eee.hku.hk | - |
dc.identifier.authority | Huang, K=rp01875 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/GLOBECOM42002.2020.9322334 | - |
dc.identifier.scopus | eid_2-s2.0-85100391477 | - |
dc.identifier.hkuros | 321261 | - |
dc.identifier.spage | 1 | - |
dc.identifier.epage | 6 | - |
dc.identifier.isi | WOS:000668970501125 | - |
dc.publisher.place | United States | - |
dc.identifier.issnl | 2334-0983 | - |