计算机科学
误码率
光谱效率
人工神经网络
干扰(通信)
正交性
带宽(计算)
正交频分复用
频分复用
块错误率
光纤
电子工程
电信
解码方法
人工智能
频道(广播)
电信线路
工程类
数学
几何学
作者
Guozhou Jiang,Jintao Wu,Mengyan Li,Liu Yang
出处
期刊:Optical Engineering
[SPIE - International Society for Optical Engineering]
日期:2022-12-19
卷期号:61 (12)
标识
DOI:10.1117/1.oe.61.12.128101
摘要
In the past few decades, many efforts have been made to solve the intercarrier interference (ICI) because of the loss of the orthogonality for the spectral efficient frequency division multiplexing (SEFDM) optical communication systems. In this paper, a deep neural network (DNN) is introduced to deal with the ICI. The intrinsic relationship between the mechanism of ICI damage and the DNN is studied and analyzed. Based on this analysis, the performance of DNN-ICI decoder compared with the conventional algorithms is demonstrated by simulation for optical SEFDM intensity modulation/direct detection (IM/DD) communication systems. The results show that the DNN-ICI decoder is greatly superior to other schemes in terms of bit error rate (BER) with a simple designed DNN under different bandwidth compression factors. Besides, the proposed methods are also robust to the fiber lengths. All the results indicate that the proposed DNN-ICI decoder has great potential to be used in SEFDM IM/DD optical systems.
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