Next Generation Optical SDM Communication System using Artificial Intelligence

DOI

10.2991/978-94-6463-754-0_30How to use a DOI?

Keywords

Quadrature phase shift keying QPSK; Orbital Angular Momentum; Deep learning Neural networks (DNNs) and Reinforcement Learning (RL); Support Vector Machines (SVM) and k-Nearest Neighbors (kNN)

Abstract

The theoretical and fundamental analysis of an advanced Orbital angular momentum (OAM) transmission system for next generation optical communication networks are represented. The proposed system implements artificial Intelligence algorithm which enhances efficiency and accuracy of OAM modulation channel transmission. The primary components of the optical transmission system is OAM encoding, multiplexing, and de-multiplexing. The theoretical OAM encoder is also said to be Vortex Generator implements spiral phase pattern to generate a helical Gaussian phase, which enable high capacity data transmission through spatial division multiplexing across multiple OAM Channels. The system implements Quadrature phase shift keying (QPSK) improves performance when combines with Artificial driven Optimization techniques. The Deep learning Neural networks (DNNs) and Reinforcement Learning (RL) play an vital role in adaptive channel selection, interference Management and error correction. The comparative study demonstrates the superiority of DNNs when compared with traditional methods such as Support Vector Machines (SVM) and k-Nearest Neighbors (k-NN). With an edge in throughput, reduced bit error rates, and improved signal-tonoise ratio in favor of DNN. Reinforcement Learning further enhances system reliability by dynamically adjusting transmission parameters in real-time. The outputs represent that AI integration does significantly improve performance and meets high-speed data and high-capacity transmission, which, in any case for the next generation, promises so much.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - P. Kavitha Thandapani
AU  - S. K. Dhinesh
AU  - N. Ashok Kumar
AU  - A. Arulmary
AU  - C. Supraja
AU  - C. Murugan
PY  - 2025
DA  - 2025/06/30
TI  - Next Generation Optical SDM Communication System using Artificial Intelligence
BT  - Proceedings of the 2025 International Conference on Advanced Research in Electronics and Communication Systems (ICARECS-2025)
PB  - Atlantis Press
SP  - 333
EP  - 348
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-754-0_30
DO  - 10.2991/978-94-6463-754-0_30
ID  - Thandapani2025
ER  -