TY - GEN
T1 - A Deep Reinforcement Learning Approach for RBMSCA in Optical Fiber Communication Networks
AU - Zhang, Xiao
AU - Tian, Qinghua
AU - Li, Zuxian
AU - Wang, Fu
AU - Tian, Feng
AU - Zhou, Sitong
AU - Zhang, Qi
AU - Xin, Xiangjun
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - A deep reinforcement learning framework is proposed to solve the problem of joint routing, modulation, band, core, and spectrum allocation in multiband, multicore elastic optical networks. The scheme outperforms several baseline reinforcement learning algorithms.
AB - A deep reinforcement learning framework is proposed to solve the problem of joint routing, modulation, band, core, and spectrum allocation in multiband, multicore elastic optical networks. The scheme outperforms several baseline reinforcement learning algorithms.
KW - deep reinforcement learning
KW - elastic optical networks
KW - resource allocation
UR - https://www.scopus.com/pages/publications/105017003771
U2 - 10.1109/ICOCN67308.2025.11145567
DO - 10.1109/ICOCN67308.2025.11145567
M3 - Conference contribution
AN - SCOPUS:105017003771
T3 - 2025 23rd International Conference on Optical Communications and Networks, ICOCN 2025
BT - 2025 23rd International Conference on Optical Communications and Networks, ICOCN 2025
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 23rd International Conference on Optical Communications and Networks, ICOCN 2025
Y2 - 28 July 2025 through 31 July 2025
ER -