Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/103849
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dc.contributorDepartment of Electrical and Electronic Engineering-
dc.creatorLiu, Sen_US
dc.creatorDu, Xen_US
dc.creatorYu, Cen_US
dc.date.accessioned2024-01-10T02:40:58Z-
dc.date.available2024-01-10T02:40:58Z-
dc.identifier.urihttp://hdl.handle.net/10397/103849-
dc.language.isoenen_US
dc.publisherOptical Society of Americaen_US
dc.rights© 2022 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement (https://opg.optica.org/library/license_v2.cfm#VOR-OA). Users may use, reuse, and build upon the article, or use the article for text or data mining, so long as such uses are for non-commercial purposes and appropriate attribution is maintained. All other rights are reserved.en_US
dc.rightsThe following publication Liu, S., Du, X., & Yu, C. (2022). H∞ filter-based dynamic joint carrier frequency offset and linear phase noise tracking for CO-OFDM systems. Optics Express, 30(23), 41157-41170 is available at https://doi.org/10.1364/OE.468086.en_US
dc.titleH∞ filter-based dynamic joint carrier frequency offset and linear phase noise tracking for CO-OFDM systemsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage41157en_US
dc.identifier.epage41170en_US
dc.identifier.volume30en_US
dc.identifier.issue23en_US
dc.identifier.doi10.1364/OE.468086en_US
dcterms.abstractIn this paper, a robust, dynamic and joint carrier frequency offset (CFO) and linear phase noise (LPN) tracking algorithm is proposed by utilizing the H 8 filter for CO-OFDM systems. The dynamic tracking is implemented by Bayesian filtering which time-recursively updates the posterior state estimates based on the prior state information and calculated gain. To improve the robustness of the dynamic tracking process against the uncertainty of the noise terms, we adopt the H 8 filter, which designs a min-max optimization problem with a performance bound-defined constraint. The H 8 filter obtains the state estimates by limiting the worst-case estimation error, which guarantees its robustness to the system uncertain noise terms and external disturbances. After the joint estimation of CFO and LPN, we then propose a decision-feedback algorithm to achieve accurate signal detection. The accuracy and robustness of the proposed algorithm are verified in an 88.9 Gb/s 16-QAM CO-OFDM system, by comparing with the conventional extended Kalman filter (EKF) and Gaussian particle filter (GPF). Simulation results show that the MSEs of CFO and LPN by H 8 filter can reach the Cramer-Rao Lower Bounds (CRLBs) as well as the Bayesian CRLB (BCRLB), and possesses excellent noise and chromatic dispersion (CD) tolerance.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationOptics express, 7 Nov. 2022, v. 30, no. 23, p. 41157-41170en_US
dcterms.isPartOfOptics expressen_US
dcterms.issued2022-11-07-
dc.identifier.isiWOS:000901327200012-
dc.identifier.scopus2-s2.0-85141514628-
dc.identifier.pmid36366600-
dc.identifier.eissn1094-4087en_US
dc.description.validate202401 bcvc-
dc.description.oaVersion of Recorden_US
dc.description.fundingSourceRGCen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextGuangdong Provincial Key Laboratory of Interdisciplinary Research and Application for Data Sciences; Guangdong Higher Education Upgrading Plan (2021-2025); National Natural Science Foundation of China; Zhuhai Basic and Applied Basic Research Foundation; UIC Research Grant Projecten_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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