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Long Haul Optical Transmission Using Multi-Channel OAM-PDM Multiplexing over HMMF-FSO Communication System

Students & Supervisors

Student Authors
Sami-ul Islam Nahid
Masters in Electrical and Electronic Engineering, FE
Arajit Saha
Masters in Electrical and Electronic Engineering, FE
Md. Shihab Sharar Oyon
Masters in Electrical and Electronic Engineering, FE
Zahid Hasan Rifat
Masters in Electrical and Electronic Engineering, FE
Supervisors
Prof. Dr. Mohammad Nasir Uddin, Peng.
Professor, Head [graduate Program], FE
Md. Kabiruzzaman
Assistant Professor, Faculty, FE
Mahmoodul Islam
Assistant Professor, Faculty, FE

Abstract

The rapid growth of data-intensive applications demands optical communication systems with higher bandwidth and improved transmission capacity. Free-space optical (FSO) links offer a compelling solution owing to their high data rates, license-free spectrum, and enhanced security. However, conventional multiplexing schemes such as wavelength-division multiplexing (WDM) and mode-division multiplexing (MDM) face limitations from crosstalk and modal dispersion, constraining further capacity enhancement. To address these challenges, this work proposes a hybrid multimode fiber/FSO (HMMF-FSO) system that integrates orbital angular momentum (OAM) multiplexing with polarization-division multiplexing (PDM). The proposed architecture employs six distinct OAM modes with dual polarization states, resulting in 12 channels and a total capacity of 120 Gbps over a single 1550 nm wavelength. Simulation results demonstrate a maximum FSO reach of 21 km under clear atmospheric conditions with an additional 1 km multimode fiber link. In adverse weather, the achievable ranges reduce to 3.25 km, 2.4 km, and 1.45 km for low, medium, and high rain, respectively, and 2.55 km, 1.66 km, and 1.32 km for light, medium, and high fog.

Keywords

Free Space Optics (FSO) Orbital Angular Momentum(OAM) Polarization Division Multiplexing

Publication Details

  • Type of Publication:
  • Conference Name: International Conference on Big Data, IoT and Machine Learning
  • Date of Conference: 25/09/2025 - 25/09/2025
  • Venue: Dhaka International University, Bangladesh
  • Organizer: Department of CSE and EEE, DIU, Bangladesh; Center for Intelligent Computing
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