Real-time, Software-Defined, GPU-Based Receiver Field Trial
Sjoerd van der Heide, Ruben S. Luis, Benjamin J. Puttnam, Georg, Rademacher, Ton Koonen, Satoshi Shinada, Yoshinari Awaji, Chigo Okonkwo,, Hideaki Furukawa
TL;DR
This paper demonstrates a real-time, GPU-based software-defined receiver operating over a metropolitan network, utilizing massive parallelization for direct-detection and coherent Kramers-Kronig detection at 2 and 1 GBaud.
Contribution
It introduces a stable, real-time GPU-based receiver capable of high-speed optical signal processing in a metropolitan network environment.
Findings
Successful real-time operation over a metropolitan network
Implementation of direct-detection and Kramers-Kronig detection at 2 and 1 GBaud
Demonstrated stability and efficiency of GPU-based processing
Abstract
We demonstrate stable real-time operation of a software-defined, GPU-based receiver over a metropolitan network. Massive parallelization is exploited for implementing direct-detection and coherent Kramers-Kronig detection in real time at 2 and 1 GBaud, respectively.
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