Machine Learning for Self-Coherent Detection Short-Reach Optical Communications
Qi Wu,
Zhaopeng Xu,
Yixiao Zhu,
Yikun Zhang,
Honglin Ji,
Yu Yang,
Gang Qiao,
Lulu Liu,
Shangcheng Wang,
Junpeng Liang,
Jinlong Wei,
Jiali Li,
Zhixue He,
Qunbi Zhuge,
Weisheng Hu
Affiliations
Qi Wu
State Key Laboratory of Advanced Optical Communication System and Networks, Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
Zhaopeng Xu
Peng Cheng Laboratory, Shenzhen 518055, China
Yixiao Zhu
State Key Laboratory of Advanced Optical Communication System and Networks, Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
Yikun Zhang
State Key Laboratory of Advanced Optical Communication System and Networks, Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
Honglin Ji
Peng Cheng Laboratory, Shenzhen 518055, China
Yu Yang
Peng Cheng Laboratory, Shenzhen 518055, China
Gang Qiao
Peng Cheng Laboratory, Shenzhen 518055, China
Lulu Liu
Peng Cheng Laboratory, Shenzhen 518055, China
Shangcheng Wang
Peng Cheng Laboratory, Shenzhen 518055, China
Junpeng Liang
Peng Cheng Laboratory, Shenzhen 518055, China
Jinlong Wei
Peng Cheng Laboratory, Shenzhen 518055, China
Jiali Li
Peng Cheng Laboratory, Shenzhen 518055, China
Zhixue He
Peng Cheng Laboratory, Shenzhen 518055, China
Qunbi Zhuge
State Key Laboratory of Advanced Optical Communication System and Networks, Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
Weisheng Hu
State Key Laboratory of Advanced Optical Communication System and Networks, Department of Electronic Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
Driven by emerging technologies such as the Internet of Things, 4K/8K video applications, virtual reality, and the metaverse, global internet protocol traffic has experienced an explosive growth in recent years. The surge in traffic imposes higher requirements for the data rate, spectral efficiency, cost, and power consumption of optical transceivers in short-reach optical networks, including data-center interconnects, passive optical networks, and 5G front-haul networks. Recently, a number of self-coherent detection (SCD) systems have been proposed and gained considerable attention due to their spectral efficiency and low cost. Compared with coherent detection, the narrow-linewidth and high-stable local oscillator can be saved at the receiver, significantly reducing the hardware complexity and cost of optical modules. At the same time, machine learning (ML) algorithms have demonstrated a remarkable performance in various types of optical communication applications, including channel equalization, constellation optimization, and optical performance monitoring. ML can also find its place in SCD systems in these scenarios. In this paper, we provide a comprehensive review of the recent progress in SCD systems designed for high-speed optical short- to medium-reach transmission links. We discuss the diverse applications and the future perspectives of ML for these SCD systems.
