Abstract:
We propose a novel energy-efficient AI-based bandwidth compensation technique that jointly optimizes Tx and Rx static filters. Experimental demonstration in a 800G system...Show MoreMetadata
Abstract:
We propose a novel energy-efficient AI-based bandwidth compensation technique that jointly optimizes Tx and Rx static filters. Experimental demonstration in a 800G system reveals gains of more than 1dB when compared with typical digital pre-emphasis.
Date of Conference: 05-09 March 2023
Date Added to IEEE Xplore: 19 May 2023
Print on Demand(PoD) ISBN:979-8-3503-1229-4