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    FSO communication system for high-speed trains under varying visibility conditions

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    1-s2.0-S2214209623000645-main.pdf (1.618Mb)
    Date
    2023-07-05
    Author
    Hasan Abbas, Al-Mohammed
    Al-Ali, Muhammed
    Yaacoub, Elias
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    Abstract
    High-speed train systems are rapidly growing in complexity and coverage, demanding efficient high-speed internet services. Existing radio frequency technology struggles to meet these demands due to handover mechanisms and limited connectivity times. Furthermore, current free-space optics (FSO) techniques require a large number of base stations (BSs), resulting in high costs. This study presents a novel high-speed train communication technique, using FSO, that significantly reduces the number of required BSs while maintaining sufficient coverage and data speeds. The proposed technique can be adapted for fixed or variable representations of transmitted and received power, providing a fixed or variable data rate. The research also investigates the impact of divergence angle on transmitted and received power. By employing the proposed communication technique, a system with a fixed data rate, such as 1.25 Gbps, can be achieved. The results demonstrate the potential of this approach in high-speed train applications, reducing the number of BSs from 113, as reported in the best existing literature, to less than 10. Weather conditions, including clear, haze, thin fog, light fog, and heavy fog, are considered when calculating the required BS locations to achieve a target data rate. Additionally, this work introduces a new handover mechanism and mathematical formulation, providing a more comprehensive solution for high-speed train communication systems. The simulations and evaluations conducted in this study are based on parameters and equations from previous works to ensure a fair comparison.
    URI
    https://www.sciencedirect.com/science/article/pii/S2214209623000645
    DOI/handle
    http://dx.doi.org/10.1016/j.vehcom.2023.100634
    http://hdl.handle.net/10576/59831
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    • Computer Science & Engineering [‎2428‎ items ]

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