Monitoring the state of polarization (SOP) in optical communication networks is vital for maintaining network reliability and performance. SOP data, influenced by environmental factors, presents significant challenges for conventional methods due to its multidimensional nature and susceptibility to noise. Machine learning (ML) algorithms provide a promising solution by effectively learning complex patterns in SOP data, thereby enhancing anomaly detection capabilities. In this paper, we introduce an enhanced vision transformer-based approach for anomaly classification and localization in SOP data. Our method leverages spectrograms derived from continuous SOP measurements and has been validated using experimental data from a 2600 km bidirectional link. The proposed approach achieves an accuracy of 99% and a timestamping precision with a root mean square error (RMSE) of 7 ms. Comparative evaluations against several ML baselines underscore the superiority of our method, particularly in accurately localizing SOP transients within spectrograms and handling overlapping events, though these are treated as single combined events. These results reaffirm the efficacy of our approach in improving anomaly classification and localization capabilities in optical networks.
{"title":"Vision Transformers for Anomaly Classification and Localization in Optical Networks Using SOP Spectrograms","authors":"Khouloud Abdelli;Matteo Lonardi;Fabien Boitier;Diego Correa;Jurgen Gripp;Samuel Olsson;Patricia Layec","doi":"10.1109/JLT.2024.3519755","DOIUrl":"https://doi.org/10.1109/JLT.2024.3519755","url":null,"abstract":"Monitoring the state of polarization (SOP) in optical communication networks is vital for maintaining network reliability and performance. SOP data, influenced by environmental factors, presents significant challenges for conventional methods due to its multidimensional nature and susceptibility to noise. Machine learning (ML) algorithms provide a promising solution by effectively learning complex patterns in SOP data, thereby enhancing anomaly detection capabilities. In this paper, we introduce an enhanced vision transformer-based approach for anomaly classification and localization in SOP data. Our method leverages spectrograms derived from continuous SOP measurements and has been validated using experimental data from a 2600 km bidirectional link. The proposed approach achieves an accuracy of 99% and a timestamping precision with a root mean square error (RMSE) of 7 ms. Comparative evaluations against several ML baselines underscore the superiority of our method, particularly in accurately localizing SOP transients within spectrograms and handling overlapping events, though these are treated as single combined events. These results reaffirm the efficacy of our approach in improving anomaly classification and localization capabilities in optical networks.","PeriodicalId":16144,"journal":{"name":"Journal of Lightwave Technology","volume":"43 4","pages":"1902-1914"},"PeriodicalIF":4.1,"publicationDate":"2024-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143438451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Space division multiplexing (SDM) has emerged as a pivotal technology for scaling the capacity of future high-capacity optical transmission systems. Large-scale multiple-input/multiple-output (MIMO) digital signal processing-based SDM systems that utilize media with inherent strong crosstalk between spatial channels, such as coupled-core multicore fibers, are particularly promising for achieving unprecedented transmission capacities. To alleviate the inherent complexity of these massively parallel systems, an SDM-MIMO signal processing scheme needs to be developed that can efficiently handle high-symbol-rate transmissions. In this context, we present a partially frozen (PF) 4D×D multiple-input/multiple-output adaptive equalizer (MIMO AEQ), tailored specifically for robust high-symbol-rate SDM-MIMO signal reception. This approach is designed to combat electrical IQ impairments—a predominant obstacle in high-symbol-rate transmission—while simultaneously enhancing tracking ability to channel dynamics and reducing computational complexity. We detail the operational principles of the PF 4D×D MIMO AEQ and validate its performance through simulations and experiments. Our results underscore its validity, demonstrating a net transmission of 2.6 (0.65×4) Tb/s/λ over a dynamically fluctuating four-coupled-core cabled transmission line using 100-Gbaud 16QAM signals.
{"title":"Coupled-Core Transmission at 100-Gbaud with Low-Complexity, Fast-Tracking 4D × D MIMO Equalizer","authors":"Akira Kawai;Kohki Shibahara;Masanori Nakamura;Takayuki Kobayashi;Takayoshi Mori;Ryota Imada;Taiji Sakamoto;Yusuke Yamada;Kazuhide Nakajima;Yutaka Miyamoto","doi":"10.1109/JLT.2024.3516787","DOIUrl":"https://doi.org/10.1109/JLT.2024.3516787","url":null,"abstract":"Space division multiplexing (SDM) has emerged as a pivotal technology for scaling the capacity of future high-capacity optical transmission systems. Large-scale multiple-input/multiple-output (MIMO) digital signal processing-based SDM systems that utilize media with inherent strong crosstalk between spatial channels, such as coupled-core multicore fibers, are particularly promising for achieving unprecedented transmission capacities. To alleviate the inherent complexity of these massively parallel systems, an SDM-MIMO signal processing scheme needs to be developed that can efficiently handle high-symbol-rate transmissions. In this context, we present a partially frozen (PF) 4D×D multiple-input/multiple-output adaptive equalizer (MIMO AEQ), tailored specifically for robust high-symbol-rate SDM-MIMO signal reception. This approach is designed to combat electrical IQ impairments—a predominant obstacle in high-symbol-rate transmission—while simultaneously enhancing tracking ability to channel dynamics and reducing computational complexity. We detail the operational principles of the PF 4D×D MIMO AEQ and validate its performance through simulations and experiments. Our results underscore its validity, demonstrating a net transmission of 2.6 (0.65×4) Tb/s/λ over a dynamically fluctuating four-coupled-core cabled transmission line using 100-Gbaud 16QAM signals.","PeriodicalId":16144,"journal":{"name":"Journal of Lightwave Technology","volume":"43 4","pages":"1941-1951"},"PeriodicalIF":4.1,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10799059","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143438437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-11DOI: 10.1109/JLT.2024.3511313
{"title":"Journal of Lightwave Technology Information for Authors","authors":"","doi":"10.1109/JLT.2024.3511313","DOIUrl":"https://doi.org/10.1109/JLT.2024.3511313","url":null,"abstract":"","PeriodicalId":16144,"journal":{"name":"Journal of Lightwave Technology","volume":"42 23","pages":"C3-C3"},"PeriodicalIF":4.1,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10794511","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142810304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-11DOI: 10.1109/JLT.2024.3511293
{"title":"Journal of Lightwave Technology Information for Authors","authors":"","doi":"10.1109/JLT.2024.3511293","DOIUrl":"https://doi.org/10.1109/JLT.2024.3511293","url":null,"abstract":"","PeriodicalId":16144,"journal":{"name":"Journal of Lightwave Technology","volume":"42 22","pages":"C3-C3"},"PeriodicalIF":4.1,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10794544","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142810387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：