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Distributed few-shot learning for intelligent recognition of communication jamming
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Liu, M., Liu, Z., Lu, W., Chen, Yunfei, Gao, X. and Zhao, N. (2022) Distributed few-shot learning for intelligent recognition of communication jamming. IEEE Journal of Selected Topics in Signal Processing, 16 (3). pp. 395-405. doi:10.1109/JSTSP.2021.3137028 ISSN 1932-4553.
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WRAP-distributed-few-shot learning-intelligent-recognition-communication-jamming-Chen-2021.pdf - Accepted Version - Requires a PDF viewer. Download (1044Kb) | Preview |
Official URL: https://doi.org/10.1109/JSTSP.2021.3137028
Abstract
Effective recognition of communication jamming is of vital importance in improving wireless communication sys- tem’s anti-jamming capability. Motivated by the major challenges that the jamming data sets in wireless communication system are often small and the recognition performance may be poor, we introduce a novel jamming recognition method based on distributed few-shot learning in this paper. Our proposed method employs a distributed recognition architecture to achieve the global optimization of multiple sub-networks by federated learn- ing. It also introduces a dense block structure in the sub-network structure to improve network information flow by the feature multiplexing and configuration bypass to improve resistance to over-fitting. Our key idea is to first obtain the time-frequency diagram, fractional Fourier transform and constellation diagram of the communication jamming signal as the model-agnostic meta-learning network input, and then train the distributed network through federated learning for jamming recognition. Simulation results show that our proposed method leads to excellent recognition performance with a small data set.
| Item Type: | Journal Article | |||||||||||||||
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| Subjects: | Q Science > QA Mathematics Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software T Technology > TK Electrical engineering. Electronics Nuclear engineering |
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| Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | |||||||||||||||
| Library of Congress Subject Headings (LCSH): | Wireless communication systems -- Security measures, Radio -- Interference, Radar -- Interference, Federated database systems, Machine learning | |||||||||||||||
| Journal or Publication Title: | IEEE Journal of Selected Topics in Signal Processing | |||||||||||||||
| Publisher: | IEEE | |||||||||||||||
| ISSN: | 1932-4553 | |||||||||||||||
| Official Date: | April 2022 | |||||||||||||||
| Dates: |
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| Volume: | 16 | |||||||||||||||
| Number: | 3 | |||||||||||||||
| Page Range: | pp. 395-405 | |||||||||||||||
| DOI: | 10.1109/JSTSP.2021.3137028 | |||||||||||||||
| Status: | Peer Reviewed | |||||||||||||||
| Publication Status: | Published | |||||||||||||||
| Reuse Statement (publisher, data, author rights): | © 2021 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. | |||||||||||||||
| Access rights to Published version: | Restricted or Subscription Access | |||||||||||||||
| Date of first compliant deposit: | 15 December 2021 | |||||||||||||||
| Date of first compliant Open Access: | 16 December 2021 | |||||||||||||||
| RIOXX Funder/Project Grant: |
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