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

2025-08-27

AI Summary

Directly modulated lasers (DMLs) exhibit complex nonlinear dynamic behavior in short-reach intensity-modulation/direct-detection (IM/DD) systems, posing significant challenges for accurate modeling and joint transceiver optimization. To address this, this paper proposes an experimental data-driven, end-to-end joint optimization framework. It constructs a data surrogate model to simultaneously optimize the pulse-shaping filter, receiver equalizer, laser bias current, and RF modulation power—enabling co-design across transmitter and receiver. Compared to conventional linear and nonlinear equalization baselines, the proposed method achieves superior bit-error-rate (BER) performance across diverse symbol rates and transmission distances, while operating at lower RF power, requiring fewer filter taps, and utilizing narrower bandwidth. This approach thus delivers both high performance and low hardware resource overhead, establishing a scalable, data-driven optimization paradigm for practical DML-based IM/DD systems.

Technology Category

• Machine Learning: Optimization
• Search and Optimization: Learning to Search
• Computer Vision: Learning & Optimization for CV

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Search and Retrieval-Augmented AI: Retrieval-Augmented Generation (RAG) and multi-modal RAG

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.

Problem

• Optimizing directly modulated laser systems for IM/DD transmission
• Addressing complex nonlinear dynamics in laser-based communication
• Improving performance with end-to-end data-driven optimization approach

Innovation

• Data-driven surrogate model for optimization
• End-to-end optimization of laser parameters
• Experimental validation with improved performance metrics