一种面向有限空芯光纤资源的异质光纤混合组网优化方法
By constructing modulation format constraints and spectrum allocation constraints, and combining Q-learning algorithms to optimize the combined deployment of hollow-core optical fibers and standard single-mode optical fibers, the channel quality assessment and network optimization problems of hybrid optical fiber networks are solved, achieving high-precision channel quality assessment and network performance improvement.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SUZHOU UNIV
- Filing Date
- 2026-05-08
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies cannot achieve accurate channel quality assessment for hybrid fiber optic networks combining hollow-core fiber and standard single-mode fiber, nor can they provide network optimization strategies that meet actual deployment needs.
Modulation format constraints, spectrum allocation constraints, and hollow fiber upgrade budget constraints are constructed. By using a hybrid fiber deployment objective function and a Q-learning reinforcement learning algorithm, the combined deployment of hollow fiber and standard single-mode fiber is optimized, the link combination is refined, and channel quality assessment and spectrum allocation are performed.
It enables high-precision channel quality assessment of heterogeneous fiber hybrid networks, provides accurate network optimization strategies, meets the engineering requirements of service transmission performance and spectrum resources, and improves network performance.
Smart Images
Figure CN122179697B_ABST