AI-Driven Hybrid RF/FSO Communication Framework for Secure Smart Grid and EV Networks under Composite Fading

Nookala Venu; Mehak Kapoor; Nitesh Patidar; Naval Kishor Sharma; Manjeet Rajput; Vikash Dhakad

doi:10.2991/978-94-6239-707-1_2

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AI-Driven Hybrid RF/FSO Communication Framework for Secure Smart Grid and EV Networks under Composite Fading

Authors

Nookala Venu¹^{, *}, Mehak Kapoor¹, Nitesh Patidar¹, Naval Kishor Sharma¹, Manjeet Rajput¹, Vikash Dhakad¹

¹Madhav Institute of Technology & Science, Deemed University (MITS-DU), Gwalior, 474005, Madhya Pradesh, India

^*Corresponding author. Email: venunookala@mitsgwalior.in

Corresponding Author

Nookala Venu

Available Online 18 June 2026.

DOI: 10.2991/978-94-6239-707-1_2 How to use a DOI?
Keywords: AI optimization; electric vehicles; free-space optics; hybrid RF/FSO; physical-layer security; smart grid
Abstract: This paper investigates a secure hybrid radio-frequency/free-space-optical (RF/FSO) communication architecture for smart grid and electric vehicle (EV) infrastructure operating under composite fading channels. An AI-driven controller based on Q-learning dynamically adapts link selection and channel parameters to maximize secrecy capacity under time-varying RF fading and atmospheric turbulence. The system is evaluated over α–η/Weibull and Gamma–Gamma channel models, reflecting realistic RF and FSO impairments. Simulation results demonstrate that the proposed adaptive hybrid scheme consistently outperforms standalone RF and FSO links in terms of secrecy capacity and robustness. The convergence behavior of the learning agent and the impact of fading parameters on secrecy performance are analyzed, highlighting the suitability of lightweight reinforcement learning for secure, adaptive smart energy communications.
Copyright: © 2026 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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Volume Title: Proceedings of the International Conference on Recent Advances in Intelligent and Sustainable Technologies (RAIST 2026)
Series: Atlantis Highlights in Intelligent Systems
Publication Date: 18 June 2026
ISBN: 978-94-6239-707-1
ISSN: 2589-4919
DOI: 10.2991/978-94-6239-707-1_2 How to use a DOI?
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.

Cite this article

ris enw bib

TY  - CONF
AU  - Nookala Venu
AU  - Mehak Kapoor
AU  - Nitesh Patidar
AU  - Naval Kishor Sharma
AU  - Manjeet Rajput
AU  - Vikash Dhakad
PY  - 2026
DA  - 2026/06/18
TI  - AI-Driven Hybrid RF/FSO Communication Framework for Secure Smart Grid and EV Networks under Composite Fading
BT  - Proceedings of the International Conference on Recent Advances in Intelligent and Sustainable Technologies (RAIST 2026)
PB  - Atlantis Press
SP  - 3
EP  - 17
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6239-707-1_2
DO  - 10.2991/978-94-6239-707-1_2
ID  - Venu2026
ER  -

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