The Bayesian-frequentist hybrid model and associated inference can combine the advantages of both Bayesian and frequentist methods and avoid their limitations. However, except for few special cases…
Machine learning (ML) has been widely used for physical layer modeling in optical networks for its high accuracy and efficient calculation structure. However, traditional ML-based methods purely re…
The coherent digital subcarrier multiplexing (DSCM) has recently been proposed as a cost saving solution to realize flexible and scalable point-to-multipoint (PTMP) networks. In this work, a hardwa…
Dynamic routing networks, aimed at finding the best routing paths in the networks, have achieved significant improvements to neural networks in terms of accuracy and efficiency. In this paper, we s…
Within a context of C+L band transmission, this work proposes a design approach for Raman pumps in hybrid fiber amplifiers (HFAs) with the goal of maximizing the total system capacity. First, the o…
In this paper, we propose to reduce the size of look-up table (LUT) for digital pre-distortion in optical communication using principal component analysis (PCA). In this scheme, the full-size LUT a…
Chromatic dispersion enhanced spectrum aliasing, a nonlinear effect in the frequency domain, is theoretically analyzed under symbol-rate sampling conditions, and the relationship between its nonlin…
In this paper, we propose a triplet-correlative perturbative nonlinearity compensation (TC-PNC) scheme to compensate for intra-channel fiber nonlinear impairments. The complexity of TC-PNC is much …
In this paper, multi-dimensional distribution matching (MDDM) based on bit-level shaping is proposed to implement probabilistic shaping (PS) for high order modulation formats. MDDM is optimized acr…
An accurate quality of transmission (QoT) estimation can help to reduce the design margin of optical network planning. The physical layer impairments (PLI) modeling can be the basis of QoT estimati…