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

该项目应用编码理论和信息理论的工具来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：在长途城际和国际光传输网络中，以及在密集的短途网络中，如在数据中心中发现的。挑战是开发编码数据传输方案，该方案(A)具有高效率，接近基本信息论极限；以及(B)可以使用以合理的能量效率运行的实用算法进行编码和解码。光纤通信网络构成了加拿大数字经济的支柱。通过互联网等数字技术开展的经济活动占加拿大总经济活动的很大一部分，而且正在迅速增长。根据加拿大统计局国民经济账户司高级分析师阿曼达·辛克莱2019年的一篇论文，科技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，占加拿大2017年经济活动总额的5.5%。COVID的流行只是强调了数字连接的重要性，因为许多员工已经过渡到在家工作，与同事进行社交距离的互动模式。三个重要特征造成了将光纤通信与其他通信技术区分开来的技术挑战：(A)每个通道的数据传输速率非常高(通常超过每个波长400 GB/S)--这严重限制了任何所提出的信号处理和解码算法的允许的复杂性；(B)目标误码率非常低(每PB一个错误)--这意味着在其他通信场景(例如无线)中允许的通信策略可能不适用于光纤通信；(C)长距离光纤信道是非线性的(脉冲在一个偏振中的传播受臭名昭著的非线性薛定谔方程的制约)--这种非线性到目前为止还没有进行准确的信息论分析，但它是限制当今系统性能的主要障碍。考虑到这些特点，本项目的总体目标是设计新的高性能低功率前向纠错(FEC)编码、整形和调制方案，专门针对非线性光纤通道进行调整。FEC子系统是光收发信机中功耗最大的模块之一。虽然软判决译码算法的性能优于硬判决算法，但即使经过精心的设计和优化，它们的功耗也要高出5到7倍。寻找在译码性能和功率消耗之间提供最佳折衷的方案是非常有意义的。

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.