Multiuser Physical-Layer Authentication Based on Latent Perturbed Neural Networks for Industrial Internet of Things-Reference-Cited by-同舟云学术

Multiuser Physical-Layer Authentication Based on Latent Perturbed Neural Networks for Industrial Internet of Things

Published:2023-01-01 Issue:1 Volume:10 Page:637-652
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Meng Rui¹^ORCID,Xu Xiaodong¹^ORCID,Sun Hao²,Zhao Hangyu¹,Wang Bizhu¹^ORCID,Han Shujun¹^ORCID,Zhang Ping¹^ORCID

Affiliation:

1. State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, China

2. Department of Broadband Communication, Peng Cheng Laboratory, Shenzhen, China

Funder

National Natural Science Foundation of China

Fundamental Research Foundation for the Central Universities

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/6488907/9997152/09873945.pdf?arnumber=9873945

Reference46 articles.

1. A Survey of Physical-Layer Authentication in Wireless Communications

2. Deep Learning for TDD and FDD Massive MIMO: Mapping Channels in Space and Frequency

3. Multiuser Physical Layer Authentication in Internet of Things With Data Augmentation

4. Deep convolutional neural networks for massive MIMO fingerprint-based positioning;vieira;Proc IEEE Int Symp Pers Indoor Mobile Radio Commun (PIMRC),2018

5. Multiple Correlated Attributes Based Physical Layer Authentication in Wireless Networks

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