Achievable Information Rates for Fiber Optics: Applications and Computations

TL;DR

This paper explores achievable information rates in fiber optic communications, comparing theoretical predictions with actual code performance, and introduces efficient computation methods and approximations for these rates.

Contribution

It introduces practical computation techniques and approximations for AIRs, enhancing the design and analysis of coded optical communication systems.

Findings

AIRs like mutual information are effective design metrics.

Comparison shows modern codes approach theoretical AIRs.

Provides closed-form approximations for AIR computations.

Abstract

In this paper, achievable information rates (AIR) for fiber optical communications are discussed. It is shown that AIRs such as the mutual information and generalized mutual information are good design metrics for coded optical systems. The theoretical predictions of AIRs are compared to the performance of modern codes including low-parity density check (LDPC) and polar codes. Two different computation methods for these AIRs are also discussed: Monte-Carlo integration and Gauss-Hermite quadrature. Closed-form ready-to-use approximations for such computations are provided for arbitrary constellations and the multidimensional AWGN channel. The computation of AIRs in optical experiments and simulations is also discussed.