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Review

A Survey on Free-Space Optical Communication with RF Backup: Models, Simulations, Experience, Machine Learning, Challenges and Future Directions

by
Sabai Phuchortham
* and
Hakilo Sabit
School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, 6-24 St. Paul Street, Private Bag 92006, Auckland 1010, New Zealand
*
Author to whom correspondence should be addressed.
Sensors 2025, 25(11), 3310; https://doi.org/10.3390/s25113310
Submission received: 4 April 2025 / Revised: 20 May 2025 / Accepted: 21 May 2025 / Published: 24 May 2025
(This article belongs to the Special Issue Sensing Technologies and Optical Communication)

Abstract

As sensor technology integrates into modern life, diverse sensing devices have become essential for collecting critical data that enables human–machine interfaces such as autonomous vehicles and healthcare monitoring systems. However, the growing number of sensor devices places significant demands on network capacity, which is constrained by the limitations of radio frequency (RF) technology. RF-based communication faces challenges such as bandwidth congestion and interference in densely populated areas. To overcome these challenges, a combination of RF with free-space optical (FSO) communication is presented. FSO is a laser-based wireless solution that offers high data rates and secure communication, similar to fiber optics but without the need for physical cables. However, FSO is highly susceptible to atmospheric turbulence and conditions such as fog and smoke, which can degrade performance. By combining the strengths of both RF and FSO, a hybrid FSO/RF system can enhance network reliability, ensuring seamless communication in dynamic urban environments. This review examines hybrid FSO/RF systems, covering both theoretical models and real-world applications. Three categories of hybrid systems, namely hard switching, soft switching, and relay-based mechanisms, are proposed, with graphical models provided to improve understanding. In addition, multi-platform applications, including autonomous, unmanned aerial vehicles (UAVs), high-altitude platforms (HAPs), and satellites, are presented. Finally, the paper identifies key challenges and outlines future research directions for hybrid communication networks.
Keywords: free-space optical; radio frequency; hybrid FSO/RF; 5G; B5G; machine learning free-space optical; radio frequency; hybrid FSO/RF; 5G; B5G; machine learning

Share and Cite

MDPI and ACS Style

Phuchortham, S.; Sabit, H. A Survey on Free-Space Optical Communication with RF Backup: Models, Simulations, Experience, Machine Learning, Challenges and Future Directions. Sensors 2025, 25, 3310. https://doi.org/10.3390/s25113310

AMA Style

Phuchortham S, Sabit H. A Survey on Free-Space Optical Communication with RF Backup: Models, Simulations, Experience, Machine Learning, Challenges and Future Directions. Sensors. 2025; 25(11):3310. https://doi.org/10.3390/s25113310

Chicago/Turabian Style

Phuchortham, Sabai, and Hakilo Sabit. 2025. "A Survey on Free-Space Optical Communication with RF Backup: Models, Simulations, Experience, Machine Learning, Challenges and Future Directions" Sensors 25, no. 11: 3310. https://doi.org/10.3390/s25113310

APA Style

Phuchortham, S., & Sabit, H. (2025). A Survey on Free-Space Optical Communication with RF Backup: Models, Simulations, Experience, Machine Learning, Challenges and Future Directions. Sensors, 25(11), 3310. https://doi.org/10.3390/s25113310

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