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Compensation Techniques for Nonlinear Effects Using NG-RoF-DSP: A Review

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Machine Learning and Mechanics Based Soft Computing Applications

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1068))

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Abstract

In a radio over fiber (RoF) transmission, the light wave transmitted through an optical fiber is modulated by the radio signal. This technique provides a better path for the transmission of wireless signals over optical media in broadband wireless networks. RoF has developed over the past three decades along with a plethora of studies in the field. However, RoF still encounters several challenges, many of which have already been overcome, yet many still need to be addressed. In newly evolving networks such as 5G and what follows, bandwidth demands, response time, jitter, and fidelity on front-end networks cause significant challenges to RoF systems. Moreover, the movement from the lower microwave scope to the microwave scope was of direct advantage to wireless operations in terms of bandwidth. However, this movement poses more challenges to RoF expansion because combining wired and a wireless (fiber) network into one basic structure is a task of considerable challenge. Therefore, this paper provides an overview of RoF technology with a specific focus on linear and nonlinear effects, mitigation methods, and a discussion of future challenges.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, Faculty of Engineering, University of Kufa, Kufa, Iraq

    Ahmed Jasim Obaid, Hassan K. Al-Musawi & Mohammed Ahmed Abdl-Nibe

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  1. Ahmed Jasim Obaid
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  2. Hassan K. Al-Musawi
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  3. Mohammed Ahmed Abdl-Nibe
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Correspondence to Ahmed Jasim Obaid .

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  1. Hanoi University of Industry, Bac Tu Liem, Hanoi, Vietnam

    Thi Dieu Linh Nguyen

  2. Department of Computer Science, University of Huddersfield, Huddersfield, UK

    Joan Lu

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Obaid, A.J., Al-Musawi, H.K., Abdl-Nibe, M.A. (2023). Compensation Techniques for Nonlinear Effects Using NG-RoF-DSP: A Review. In: Nguyen, T.D.L., Lu, J. (eds) Machine Learning and Mechanics Based Soft Computing Applications. Studies in Computational Intelligence, vol 1068. Springer, Singapore. https://doi.org/10.1007/978-981-19-6450-3_26

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  • DOI: https://doi.org/10.1007/978-981-19-6450-3_26

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