A review on deep learning autoencoder in the design of next-generation communication systems

O Alnaseri, L Alzubaidi, Y Himeur… - arxiv preprint arxiv …, 2024 - arxiv.org
Traditional mathematical models used in designing next-generation communication systems
often fall short due to inherent simplifications, narrow scope, and computational limitations …

Recent Advances on Machine Learning-aided DSP for Short-reach and Long-haul Optical Communications

L Schmalen, V Lauinger, J Ney, N Wehn… - arxiv preprint arxiv …, 2024 - arxiv.org
arxiv:2411.10101v1 [eess.SP] 15 Nov 2024 Page 1 Recent Advances on Machine Learning-aided
DSP for Short-reach and Long-haul Optical Communications Laurent Schmalen,1,* Vincent …

[HTML][HTML] Machine learning opportunities for integrated polarization sensing and communication in optical fibers

A Rode, M Farsi, V Lauinger, M Karlsson, E Agrell… - Optical Fiber …, 2025 - Elsevier
As the bedrock of the Internet, optical fibers are ubiquitously deployed and historically
dedicated to ensuring robust data transmission. Leveraging their extensive installation …

Neural-network-based carrier-less amplitude phase modulated signal generation and end-to-end optimization for fiber-terahertz integrated communication system

C Huang, L Tao, Z Li, J Jia, B Dong, S ** Robust to Semiconductor Laser Noise and Nonlinearity in Fiber-THz System
X Liu, J Zhang, M Zhu, Z **-based coherent WDM optical fiber communication system supported by deep-learning autoencoder
AM Abbass, RS Fyath - Results in Optics, 2024 - Elsevier
Geometric constellation sha** (GCS) has been proposed to enhance the performance of
wavelength-division multiplexing (WDM) coherent optical fiber communication (OFC) …