Large-capacity and long-haul photonic networks

2015 Fiscal Year Final Research Report

• Project/Area Number: 26820141
• Research Category: Grant-in-Aid for Young Scientists (B)
• Allocation Type: Multi-year Fund
• Research Field: Communication/Network engineering
• Research Institution: Nagoya University
• Principal Investigator: MORI Yojiro 名古屋大学, 工学(系)研究科(研究院), 助教 (10722100)
• Project Period (FY): 2014-04-01 – 2016-03-31
• Keywords: 光ファイバ通信 / 光ネットワーク / 機械学習

Outline of Final Research Achievements

In optical fiber communication systems, the transmissible capacity and distance are strictly limited by transmission impairments such as fiber nonlinearity in links. To maximize network performance, signal distortion caused by such impairments must be eliminated. Machine learning can discriminate symbols in accordance with their distortion. As a result, the demodulation performance can be improved. However, cycle slips induced by laser phase noise disrupt the learning process and hence constructed decision boundaries are distorted. To resolve this problem, we propose a novel configuration in which cycle-slip detection and correction are introduced into the machine learning process. With such a scheme, we can reduce the number of bit errors in a stable manner. The proposed scheme substantially elongate the transmissible distance without reducing capacity.

Free Research Field

通信工学，ネットワーク，ディジタル信号処理