Coding, Shaping, and Modulation for High-Throughput Fiber-Optic Communication

该项目应用编码理论和信息论的工具，以提高在两个不同距离尺度上运行的光纤通信网络的信息承载能力：在长途城市间和国际光传输网络中，以及在数据中心的密集短途网络中。面临的挑战是开发编码数据传输方案(a)具有高效率，接近基本信息论极限；并且(b)可以用具有合理能效的实用算法进行编码和解码。光纤通信网络是加拿大数字经济的支柱。通过互联网等数字技术进行的经济活动代表了加拿大总体经济活动中很大且快速增长的一部分。根据加拿大统计局国民经济核算部高级分析师阿曼达·辛克莱2019年的一篇论文，技术和互联网“从根本上改变了”加拿大人和加拿大企业的互动方式。辛克莱报告称，与数字经济相关的国内生产总值接近1100亿美元，占2017年加拿大经济活动总量的5.5%。新冠疫情凸显了数字连接的重要性，因为许多员工已经过渡到在家工作，与同事保持社交距离的互动模式。光纤通信与其他通信技术的区别在于三个重要的特点：(a)每通道数据传输速率非常高（通常超过每波长400 Gb/s）——这严重限制了任何提议的信号处理和解码算法的允许复杂性；(b)目标误码率非常低（每千兆比特一个错误）——这意味着在其他通信场景（如无线）中允许的通信策略可能不适用于光纤通信；(c)长距离光纤通道是非线性的（脉冲在一个偏振方向上的传播是由臭名昭著的非线性Schrödinger方程控制的）——非线性迄今为止无法进行精确的信息论分析，但它是限制当今系统性能的主要缺陷。考虑到这些特性，本项目的总体目标是设计新的高性能低功耗前向纠错（FEC）编码、整形和调制方案，专门针对非线性光纤通道进行调谐。FEC子系统是光收发器中功耗最大的模块之一。虽然软判决译码算法比硬判决译码算法性能优越，但即使经过精心设计和优化，它们的功耗也是硬判决译码算法的5到7倍。找到在解码性能和功耗之间提供最佳折衷的方案是非常有趣的。

This project applies the tools of coding theory and information theory to improve the information-carrying capacity of fiber-optic communication networks operating at two different distance scales: in long-haul inter-urban and international optical transport networks, and in dense short-haul networks as found in data centres. The challenge is to develop coded data transmission schemes that (a) have high efficiency, approaching fundamental information-theoretic limits; and (b) can be encoded and decoded with practical algorithms operating with reasonable energy efficiency. Fiber-optic communication networks form the backbone of Canada's digital economy. The economic activity conducted through digital technologies such as the Internet, represents a large-and rapidly growing-part of Canada's total economic activity. According to a 2019 paper of Amanda Sinclair, senior analyst of the National Economic Accounts Division of Statistics Canada, technology and the Internet have "fundamentally changed" how Canadians and Canadian businesses interact. Sinclair reported that the gross domestic product connected to the digital economy was nearly $110 billion, representing 5.5 per cent of Canada's total economic activity in 2017. The COVID pandemic has only underscored the importance of digital connectivity as many workers have transitioned to working from home with socially-distanced modes of interaction with co-workers. Three important characteristics create technical challenges that distinguish fiber-optic communications from other communications technologies: (a) per-channel data transmission rates are very high (often exceeding 400 Gb/s per wavelength)-this severely constrains the allowable complexity of any proposed signal processing and decoding algorithms; (b) the target bit error probability is very low (one error per petabit)-this means that communication strategies allowable in other communication scenarios (such as wireless) may not be applicable to fiber-optic communications; (c) the long-haul fiber-optic channel is nonlinear (pulse propagation in one polarization is governed by the notorious nonlinear Schrödinger equation)-the nonlinearity has so far defied exact information-theoretic analysis, yet it is the dominant impairment limiting the performance of today's systems. Keeping these characteristics in mind, the overall aim of this project is to design new high-performance low-power forward error-correction (FEC) coding, shaping, and modulation schemes specifically tuned for nonlinear fiber-optic channels. The FEC subsystem is one of the most power-consuming modules in optical transceivers. While soft-decision decoding algorithms have superior performance compared with hard-decision algorithms, they consume a factor of 5 to 7 times more power, even with careful design and optimization. It is of great interest to find schemes that provide the best trade offs between decoding performance and power consumption.