Increasing bandwidth requirements have posed significant challenges for traditional access networks. It is difficult for intensity modulation/direct detection to meet the power budget and flexibility requirements of the next-generation passive optical network (PON) at 100G and beyond considering the new requirements. This is driving researchers to develop novel optical access technologies. Low-cost, wide-coverage, and high-flexibility coherent PON is emerging as a strong contender in the competition. In this article, we will review technologies that reduce the complexity of coherent PON (CPON), enabling it to meet the commercial requirements. Also, advanced algorithms and architectures that can enhance system coverage and flexibility are also discussed.

This paper experimentally demonstrates a distributed photonics-based W-band integrated sensing and communication (ISAC) system, in which radar sensing can aid the communication links in alignment and data rate estimation. As a proof-of-concept, the ISAC system locates the users, guides the alignment, and sets a communication link with the estimated highest data rate. A peak net data rate of 68.6 Gbit/s and a target sensing with a less-than-1-cm error and a sub-2-cm resolution have been tested over a 10-km fiber and a 1.15-m free space transmission in the photonics-based W-band ISAC system. The achievable net data rates of the users at different locations estimated by sensing are experimentally verified.

相比于传统的强度调制/直接检测（IM/DD）系统，相干系统具有更高的容量和功率预算，能更好地满足高容量无源光网络（PON）的需求。近年来，如何将相干应用于PON场景以更好地支撑未来高带宽业务已成为研究热点。文章从系统架构、相干简化、上行突发模式检测以及灵活PON 4个方面对相干PON关键技术研究现状进行了总结，并展望提出了激光共享上下行滤波器组多载波（FBMC）-PON和半导体光放大器（SOA）电流调控灵活PON方案。

2021年国际电联电信标准化部门（ITU-T）完成50 Gbit/s无源光网络（PON）的标准制定，当前设备商和运营商已经完成样机验证，ITU-T成立Beyond 50 Gbit/s PON讨论组开始研讨未来PON相关技术方案，因此Beyond 50 Gbit/s PON成为当前光通信领域的研究热点。根据前几代PON标准的速率演进规律推测，Beyond 50 Gbit/s PON的速率预计将超过100 Gbit/s。文章将分析超100 Gbit/s PON面临的问题和挑战，重点介绍灵活速率PON和相干PON架构这两个潜在技术路径及其关键技术方案，为未来超100 Gbit/s PON的研究和标准制定提供参考。

提出一种基于目标检测算法的柔性浅埋物的声-振智能探测方法，将声波激励、激光散斑干涉测振和目标检测算法有机结合，用以柔性浅埋物的大范围快速探测。在论述YOLO系列目标检测算法原理的基础上，选择并优化柔性浅埋物的智能探测网络模型；然后，搭建声-光融合智能探测系统，构建不同柔性浅埋物的激光散斑干涉条纹图数据集；最后，对数据集进行训练和测试，验证该算法用于干涉条纹图识别的可行性。实验结果表明：在给定实验条件下，柔性浅埋物智能探测网络模型的精确率为98.39%，召回率为84.72%，平均识别精度为99.66%。该声-振智能探测方法可以在给定实验环境下对多种柔性浅埋物的激光散斑干涉条纹图进行智能识别，适用于浅层地下柔性掩埋物的大面积快速探测。

Curvature sensing plays an important role in structural health monitoring, damage detection, real-time shape control, modification, etc. Developing curvature sensors with large measurement ranges, high sensitivity, and linearity remains a major challenge. In this study, a curvature sensor based on flexible one-dimensional photonic crystal (1D-PC) films was proposed. The flexible 1D-PC films composed of dense chalcogenide glass and water-soluble polymer materials were fabricated by solution processing. The flexible 1D-PC film curvature sensor has a wide measurement range of 33–133 m^-1 and a maximum sensitivity of 0.26 nm/m^-1. The shift of the transmission peak varies approximately linearly with the curvature in the entire measurement range. This kind of 1D-PC film curvature sensor provides a new idea for curvature sensing and measurement.