Title:
METHOD FOR ALIGNING GRADIENT SYMBOLS BY USING BIAS REGARDING AIRCOMP IN SIGNAL AMPLITUDE RANGE OF RECEIVER
Document Type and Number:
WIPO Patent Application WO/2022/050466
Kind Code:
A1
Abstract:
Disclosed is a method for aligning gradient symbols by using bias regarding AirComp in a signal amplitude range of a receiver. A method for aligning gradient symbols according to an embodiment of the present specification comprises the steps of: performing iteration of gradient values included in a first planar vector and applying clipping and bias values so as to obtain a second planar vector having gradient values in which symbols are aligned; and transmitting the second planar vector together with channel information to a server in the form of AirComp. Various embodiments of the present specification may be linked to an artificial intelligence module, a drone (unmanned aerial vehicle, UAV), a robot, an augmented reality (AR) device, a virtual reality (VR) device, a device related to a 5G service, and the like.
Inventors:
JEON KIJUN (KR)
LEE SANGRIM (KR)
LEE HOJAE (KR)
KIM YEONGJUN (KR)
KIM SUNGJIN (KR)
LEE SANGRIM (KR)
LEE HOJAE (KR)
KIM YEONGJUN (KR)
KIM SUNGJIN (KR)
Application Number:
PCT/KR2020/012060
Publication Date:
March 10, 2022
Filing Date:
September 07, 2020
Export Citation:
Assignee:
LG ELECTRONICS INC (KR)
International Classes:
G06N20/20; G06N3/04; G06N3/08; H04B7/024; H04B17/318
Foreign References:
| US20190205745A1 | 2019-07-04 | |||
| KR20200104734A | 2020-09-04 |
Other References:
YUSUKE KODA; KOJI YAMAMOTO; TAKAYUKI NISHIO; MASAHIRO MORIKURA: "Differentially Private AirComp Federated Learning with Power Adaptation Harnessing Receiver Noise", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, 14 April 2020 (2020-04-14), 201 Olin Library Cornell University Ithaca, NY 14853 , XP081895705, DOI: 10.1109/GLOBECOM42002.2020.9322199
GUANGXU ZHU; YUQING DU; DENIZ GUNDUZ; KAIBIN HUANG: "One-Bit Over-the-Air Aggregation for Communication-Efficient Federated Edge Learning: Design and Convergence Analysis", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, 16 January 2020 (2020-01-16), 201 Olin Library Cornell University Ithaca, NY 14853 , XP081579991
NAIFU ZHANG; MEIXIA TAO: "Gradient Statistics Aware Power Control for Over-the-Air Federated Learning in Fading Channels", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, 4 March 2020 (2020-03-04), 201 Olin Library Cornell University Ithaca, NY 14853 , XP081614135
GUANGXU ZHU; YUQING DU; DENIZ GUNDUZ; KAIBIN HUANG: "One-Bit Over-the-Air Aggregation for Communication-Efficient Federated Edge Learning: Design and Convergence Analysis", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, 16 January 2020 (2020-01-16), 201 Olin Library Cornell University Ithaca, NY 14853 , XP081579991
NAIFU ZHANG; MEIXIA TAO: "Gradient Statistics Aware Power Control for Over-the-Air Federated Learning in Fading Channels", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, 4 March 2020 (2020-03-04), 201 Olin Library Cornell University Ithaca, NY 14853 , XP081614135
Attorney, Agent or Firm:
ROYAL PATENT & LAW OFFICE (KR)
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