Report

Teaser, summary, work performed and final results

Periodic Reporting for period 1 - TERA (Coding for terabit-per-second fiber-optical communications)

Teaser

Long-haul fiber-optic communication links carry virtually all intercontinental data traffic and are often referred to as the Internet backbone. In order to cope with the ever-increasing traffic demands due to Internet services such as video streaming or cloud computing...

Summary

Long-haul fiber-optic communication links carry virtually all intercontinental data traffic and are often referred to as the Internet backbone. In order to cope with the ever-increasing traffic demands due to Internet services such as video streaming or cloud computing, next-generation systems are soon required to adopt data rates in the order of terabits per second. The overall goal of this project is to enable the design of reliable and sustainable fiber-optic communication systems that operate at terabit-per-second data rates. To that end, we study both decoding and equalization algorithms for such systems. The purpose of these algorithms is (i) to ensure reliable data transmission in the presence of noise (in the case of decoding) and (ii) to compensate for propagation impairments such as chromatic dispersion and Kerr nonlinearities (in the case of equalization). One specific objective of this project is to derive effective theoretical tools that allow for a rapid assessment of the code performance as a function of its design parameters. Such tools are crucial in order to make informed system design choices without the need for extensive numerical simulations. Another objective is to address the growing problem of energy consumption in fiber-optic systems by designing low-complexity receiver algorithms. The results and theoretical insights obtained in this project will help to ensure that future data traffic demands are met in a sustainable way.

Work performed

So far, our work has mainly focused on the development of low-complexity receiver algorithms. In particular, we have proposed a novel decoding algorithm called anchor decoding, which can be applied to a wide variety of practical code constructions that are currently used in fiber-optical systems. The algorithm offers state-of-the-art performance based on computationally efficient hard-decision decoding. Furthermore, we have developed new decoding approaches for Reed-Muller codes, which are a classic family of codes that exhibit a rich algebraic structure. We have also explored new data-driven paradigms for both code design and decoding algorithms based on an end-to-end machine learning autoencoder approach. Other main project results include the identification of a fundamental relationship between a popular existing nonlinear equalization strategy (called digital backpropagation) and conventional feed-forward artificial neural networks. Based on this relationship, we have proposed a novel algorithm, which can significantly reduce the complexity compared to the previous state-of-the-art, without sacrificing performance. The new algorithm has been implemented and verified under realistic hardware assumptions. Finally, we have identified a so-called finite-length scaling law for a specific code class relevant for fiber-optic transmission. This scaling law allows for rapid prediction of the code performance as a function of the code length. A comprehensive overview and more information about exploitation and dissemination activities will be provided at the end of the project.

Final results

The main motivating driving force behind this research is the design of next-generation fiber-optic systems. The design of such systems will require assessment of nontrivial trade-offs between several key system parameters such as performance and complexity. The theoretical tools derived in this project will be of great practical importance in this context. They can be used for example to rapidly assess the code performance without the need to run time-consuming simulations, guide the selection of suitable system parameters to optimize the overall system performance, and find novel code classes that outperform existing code classes. This project also aims to address the growing problem of energy-consumption in fiber-optic systems by designing state-of-the-art receiver algorithms. The Internet, along with its associated fiber-optic infrastructure consumes a significant fraction of the world-wide electrical energy production. With the rapidly increasing data traffic, this fraction is bound to increase, unless a significant effort is made to ensure that optical data transport becomes more energy efficient. The results and theoretical insights obtained in this project will help to ensure that future data traffic demands are met in a sustainable way.

Website & more info

More info: http://www.christianhaeger.de/projects.html.