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<p>The present work explores the efficacy of the hybrid compensator combining deep neural network and random forest (DNN-RF) for mitigation of the multiple impairments generally observed in the coherent optical orthogonal frequency division multiplexing (CO-OFDM) system. This proposed DNN-RF algorithm is providing more faster, accurate, and robust results as compared to DNN algorithm for complex data. Further, the performance of the proposed methodology was evaluated with and without low density parity checker (LDPC) code. The LDPC is used in this work in order to reduce the computational complexity by simplifying the coding processes using the sparse parity-check matrices. For quantitative evaluation of the system, standard performance metrics such as Q-factor, bit error rate (BER) were calculated over different values of launch power and transmission distance. Additionally, keeping in the view the network security, quantum noise stream cipher (QNSC) encryption was used to offer higher security during the long-range transmission over the optical fiber. This paper shows that the proposed method is highly efficient to simultaneously compensating the multiple impairments with more decoding speed in comparison to traditional techniques.</p>

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Synergistic effect of DNN-random forest based compensator for suppression of multiple impairments in CO-OFDM system

  • 期刊论文

  • 发表日期：

    2025年6月28日

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  • Gurpreet Kaur,
  • Gurmeet Kaur

摘要

The present work explores the efficacy of the hybrid compensator combining deep neural network and random forest (DNN-RF) for mitigation of the multiple impairments generally observed in the coherent optical orthogonal frequency division multiplexing (CO-OFDM) system. This proposed DNN-RF algorithm is providing more faster, accurate, and robust results as compared to DNN algorithm for complex data. Further, the performance of the proposed methodology was evaluated with and without low density parity checker (LDPC) code. The LDPC is used in this work in order to reduce the computational complexity by simplifying the coding processes using the sparse parity-check matrices. For quantitative evaluation of the system, standard performance metrics such as Q-factor, bit error rate (BER) were calculated over different values of launch power and transmission distance. Additionally, keeping in the view the network security, quantum noise stream cipher (QNSC) encryption was used to offer higher security during the long-range transmission over the optical fiber. This paper shows that the proposed method is highly efficient to simultaneously compensating the multiple impairments with more decoding speed in comparison to traditional techniques.