The demand for network capacity has been steadily increasing in recent decades due to the
growth of new digital applications and services. Optical fiber supports to solve and avoid …

Derived from the regular perturbation treatment of the nonlinear Schrödinger equation, a
machine learning-based scheme to mitigate the intra-channel optical fiber nonlinearity is …

The first-order (FO) perturbation theory-based nonlinearity compensation (PB-NLC)
technique has been widely investigated to combat the detrimental effects of the intra …

A normalized batch gradient descent optimizer is proposed to improve the first-order regular
perturbation coefficients of the Manakov equation, often referred to as kernels. The …

Several machine learning inspired methods for perturbation-based fiber n onlinearity
(PBNLC) compensation have been presented in recent literature. We critically revisit …

Kerr nonlinearity in long distance fiber-optic link imposes a fundamental limitation to the
capacity of wavelength division multiplexed (WDM) optical communication systems. Solving …

In the efficient implementation of perturbation theory-based nonlinearity compensation
method for reliable fiber-optic coherent communication systems, different quantization …

Fiber nonlinearity is the bottleneck of optical communication systems and is commonly
addressed by applying various nonlinearity mitigation and compensation techniques. In …

Fiber nonlinearity effects cap achievable rates and ranges in long-haul optical fiber
communication links. Conventional nonlinearity compensation methods, such as …

Fiber nonlinearity or what know as (Kerr effects) has become a major limiting transmission
impairment factor and channel capacity of high-speed optical communication systems. The …