A Multi-Carrier Deep Learning CSK Communication System
A new Multi-Carrier Deep Learning Chaos Shift Keying (MC-DLCSK) modulation is designed in this letter. The proposed receiver includes a Neural Network (NN)-based classifier that recovers MC-DLCSK signals. The results demonstrate that the MC-DLCSK system achieves a considerable Bit Error Rate (BER) gain compared to all existing similar systems under both Additive White Gaussian Noise (AWGN) and Rayleigh fading channels.
Authors
- Georges Kaddoum (ORCID: https://orcid.org/0000-0002-5025-6624)
- Marijan Herceg (ORCID: https://orcid.org/0000-0003-4812-0493)
- Majid Mobini (ORCID: https://orcid.org/0000-0003-2514-7490)
Institutions
- Xenobe Research Institute (US)
- University of Osijek (HR)
- Babol Noshirvani University of Technology (IR)
Publication Details
- Journal
- IEEE Communications Letters
- Published
- 2025-03-31
- DOI
- https://doi.org/10.1109/lcomm.2025.3556474
- Primary Topic
- Wireless Signal Modulation Classification
- Type
- article
- Field-Weighted Citation Impact
- 0.00