F. M. Alsalami, S. Rajbhandari, Zahir Ahmad, D. Grace
{"title":"Scalar Minimax Filter-based Phase Tracking for Continuous-Variable Quantum Key Distribution","authors":"F. M. Alsalami, S. Rajbhandari, Zahir Ahmad, D. Grace","doi":"10.1109/CSNDSP54353.2022.9907992","DOIUrl":null,"url":null,"abstract":"In local oscillator (LLO)-based continuous-variable quantum key distribution (CV-QKD), a difference between the linewidth values of two free-running lasers at Alice and Bob induces a phase drift noise. This work proposes a novel minimax filter-based phase tracking that aims to minimize the phase drift considering maximum residual phase error to achieve optimal phase estimation. Simulation results show that the minimax filter offers a lower phase estimation mean square error (MSE) value compared to the Kalman filter when worst-case phase drift error due to high linewidth difference or high measurement noise values are considered.","PeriodicalId":288069,"journal":{"name":"2022 13th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP)","volume":"46 2","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 13th International Symposium on Communication Systems, Networks and Digital Signal Processing (CSNDSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSNDSP54353.2022.9907992","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In local oscillator (LLO)-based continuous-variable quantum key distribution (CV-QKD), a difference between the linewidth values of two free-running lasers at Alice and Bob induces a phase drift noise. This work proposes a novel minimax filter-based phase tracking that aims to minimize the phase drift considering maximum residual phase error to achieve optimal phase estimation. Simulation results show that the minimax filter offers a lower phase estimation mean square error (MSE) value compared to the Kalman filter when worst-case phase drift error due to high linewidth difference or high measurement noise values are considered.