# An Achievable Rate for an Optical Channel with Finite Memory

## TL;DR

This paper models a fiber optic channel with finite memory, providing an improved achievable capacity bound that accounts for Kerr nonlinearity, advancing understanding beyond simple Gaussian noise models.

## Contribution

It introduces a finite-memory model for optical channels and derives a tighter capacity bound considering Kerr nonlinearity effects.

## Key findings

- Derived an achievable capacity bound for finite-memory optical channels.
- Showed the new bound improves upon previous models.
- Enhanced understanding of nonlinear effects in fiber optics.

## Abstract

A fiber optic channel is modeled in a variety of ways; from the simple additive white complex Gaussian noise model, to models that incorporate memory in the channel. Because of Kerr nonlinearity, a simple model is not a good approximation to an optical fiber. Hence we study a fiber optic channel with finite memory and provide an achievable bound on channel capacity that improves upon a previously known bound.