Automatic modulation recognition via aligned signals and key features. Issue 1 (12th December 2022)
- Record Type:
- Journal Article
- Title:
- Automatic modulation recognition via aligned signals and key features. Issue 1 (12th December 2022)
- Main Title:
- Automatic modulation recognition via aligned signals and key features
- Authors:
- Liu, Fugang
Pan, Jingyi
Zhou, Ruolin
Jiang, Xiaolin - Abstract:
- Abstract: Deep learning‐based classification algorithms have been used for automatic modulation recognition (AMR). However, most methods only focus on end‐to‐end mapping and neglect the classic key features. In this paper, signals are enforced with key classification features to propose a novel deep learning AMR model by learning the shared latent space of the aligned signals and key features (LLAF); this increases the generalizability of the model and ensures the physical plausibility of the results. To obtain adequate signal representations, an encoder–decoder architecture is proposed to learn the shared latent space, and the architecture is trained to approximate prior label distributions for precise signal classification. Simulation results verify the high recognition accuracy of the proposed LLAF model under different signal‐to‐noise ratios (SNRs).
- Is Part Of:
- Electronics letters. Volume 59:Issue 1(2023)
- Journal:
- Electronics letters
- Issue:
- Volume 59:Issue 1(2023)
- Issue Display:
- Volume 59, Issue 1 (2023)
- Year:
- 2023
- Volume:
- 59
- Issue:
- 1
- Issue Sort Value:
- 2023-0059-0001-0000
- Page Start:
- n/a
- Page End:
- n/a
- Publication Date:
- 2022-12-12
- Subjects:
- Electronics -- Periodicals
621.381 - Journal URLs:
- http://digital-library.theiet.org/content/journals/el ↗
http://estar.bl.uk/cgi-bin/sciserv.pl?collection=journals&journal=00135194 ↗
https://ietresearch.onlinelibrary.wiley.com/loi/1350911x ↗
http://www.theiet.org/ ↗ - DOI:
- 10.1049/ell2.12697 ↗
- Languages:
- English
- ISSNs:
- 0013-5194
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3705.060000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 25005.xml