Optical Communication Technology, Volume. 48, Issue 3, 23(2024)

Spectrum allocation algorithm for C+L band elastic optical networks based on deep reinforcement learning

YAN Dan1...2, FENG Nan3,4, ZUO Xiaobo1,2, SHEN Lingfei1,2, REN Danping1,2, HU Jinhua1,2, and ZHAO Jijun12 |Show fewer author(s)
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  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
  • 4[in Chinese]
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    Aiming at the problem of intensified physical layer damage caused by stimulated Raman scattering (SRS) effect in C+L band elastic optical networks, a spectrum allocation algorithm based on deep reinforcement leaming (DRL) adaptive modulation format is proposed. In the routing stage, the K-shortest routing algorithm is used to pre calculate K shortest candidate paths for business requests. In the stages of band, modulation format, and spectrum allocation, DRL is used for intelligent decision-making, and two reward functions are combined to reduce network blocking rate and improve spectrum utilization efficiency. The simulation results show that the algorithm can effectively reduce blocking rate and improve spectrum utilization.

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    YAN Dan, FENG Nan, ZUO Xiaobo, SHEN Lingfei, REN Danping, HU Jinhua, ZHAO Jijun. Spectrum allocation algorithm for C+L band elastic optical networks based on deep reinforcement learning[J]. Optical Communication Technology, 2024, 48(3): 23

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    Paper Information

    Received: Jan. 2, 2024

    Accepted: --

    Published Online: Aug. 2, 2024

    The Author Email:

    DOI:10.13921/j.cnki.issn1002-5561.2024.03.005

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