# Experimental End-to-End Optimization of Directly Modulated Laser-based IM/DD Transmission

## TL;DR

This paper presents a data-driven end-to-end optimization approach for DML-based IM/DD systems, improving performance and efficiency by jointly optimizing system parameters based on experimental data.

## Contribution

It introduces a novel end-to-end optimization framework for DML systems using a surrogate model trained on experimental data, outperforming traditional benchmark schemes.

## Key findings

- Enhanced transmission performance across various symbol rates and distances.
- Reduced RF power and filter complexity in optimized systems.
- Superior results compared to linear and nonlinear benchmark schemes.

## Abstract

Directly modulated lasers (DMLs) are an attractive technology for short-reach intensity modulation and direct detection communication systems. However, their complex nonlinear dynamics make the modeling and optimization of DML-based systems challenging. In this paper, we study the end-to-end optimization of DML-based systems based on a data-driven surrogate model trained on experimental data. The end-to-end optimization includes the pulse shaping and equalizer filters, the bias current and the modulation radio-frequency (RF) power applied to the laser. The performance of the end-to-end optimization scheme is tested on the experimental setup and compared to 4 different benchmark schemes based on linear and nonlinear receiver-side equalization. The results show that the proposed end-to-end scheme is able to deliver better performance throughout the studied symbol rates and transmission distances while employing lower modulation RF power, fewer filter taps and utilizing a smaller signal bandwidth.