{"created":"2023-10-18T23:48:38.586823+00:00","id":2000106,"links":{},"metadata":{"_buckets":{"deposit":"022b4727-709b-4b14-b3fb-496d995d2d8b"},"_deposit":{"created_by":17,"id":"2000106","owner":"17","owners":[17],"pid":{"revision_id":0,"type":"depid","value":"2000106"},"status":"published"},"_oai":{"id":"oai:ynu.repo.nii.ac.jp:02000106","sets":["1006:1009"]},"author_link":[],"control_number":"2000106","item_2_biblio_info_8":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2023-10-12","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"12","bibliographicVolumeNumber":"27","bibliographic_titles":[{"bibliographic_title":"IEEE Communications Letters","bibliographic_titleLang":"en"}]}]},"item_2_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"This letter considers a data-driven approach to a secret key rate analysis of physical layer secret key generation based on mutual information neural estimator (MINE), which achieves the state-of-the-art estimation accuracy. Since MINE does not require any statistical knowledge of randomness sources, the proposed approach is applicable to any source model and even real data which cannot be fully expressed by a simple model. We first demonstrate by simulations that the proposed estimation provides good approximations to the theoretical secret key rate for a simple model, and then show that the achievable secret key rate highly depends on sources of randomness and employed channel estimation schemes for a realistic wireless channel model. As an application of our analysis, we present a method to train quantization through backpropagation that maximizes the estimated secret key rate.","subitem_description_language":"en","subitem_description_type":"Abstract"}]},"item_2_publisher_35":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"Institute of Electrical and Electronics Engineers"}]},"item_2_relation_13":{"attribute_name":"DOI","attribute_value_mlt":[{"subitem_relation_type":"isVersionOf","subitem_relation_type_id":{"subitem_relation_type_id_text":"https://doi.org/10.1109/LCOMM.2023.3323957","subitem_relation_type_select":"DOI"}}]},"item_2_rights_14":{"attribute_name":"権利","attribute_value_mlt":[{"subitem_rights":"© 2023 IEEE.  Personal use of this material is permitted.  Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.","subitem_rights_language":"en","subitem_rights_resource":"https://journals.ieeeauthorcenter.ieee.org/become-an-ieee-journal-author/publishing-ethics/guidelines-and-policies/post-publication-policies/"}]},"item_2_source_id_11":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11114040","subitem_source_identifier_type":"NCID"}]},"item_2_source_id_9":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"15582558","subitem_source_identifier_type":"EISSN"}]},"item_2_version_type_18":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_ab4af688f83e57aa","subitem_version_type":"AM"}]},"item_access_right":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"embargoed access","subitem_access_right_uri":"http://purl.org/coar/access_right/c_f1cf"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorAffiliations":[{"affiliationNames":[{"affiliationName":"Institute of Advanced Sciences, Yokohama National University","affiliationNameLang":"en"}]}],"creatorNames":[{"creatorName":"Toshiki, Matsumine","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"0000-0001-9583-8129","nameIdentifierScheme":"ORCID","nameIdentifierURI":"https://orcid.org/0000-0001-9583-8129"}]},{"creatorAffiliations":[{"affiliationNames":[{"affiliationName":"Department of Electrical and Computer Engineering, Yokohama National University"}]}],"creatorNames":[{"creatorName":"Hideki, Ochiai","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"0000-0001-9303-5250","nameIdentifierScheme":"ORCID","nameIdentifierURI":"https://orcid.org/0000-0001-9303-5250"}]},{"creatorAffiliations":[{"affiliationNames":[{"affiliationName":"Graduate School of Environment and Information Sciences, Yokohama National University"}]}],"creatorNames":[{"creatorName":"Junji, Shikata","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"0000-0003-2861-359X","nameIdentifierScheme":"ORCID","nameIdentifierURI":"https://orcid.org/0000-0003-2861-359X"}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2025-10-13"}],"displaytype":"detail","fileDate":[{"fileDateType":"Issued","fileDateValue":"2023-10-12"}],"filename":"LCOMM3323957.pdf","filesize":[{"value":"382 KB"}],"format":"application/pdf","mimetype":"application/pdf","url":{"objectType":"fulltext","url":"https://ynu.repo.nii.ac.jp/record/2000106/files/LCOMM3323957.pdf"},"version_id":"67f2bb69-b56c-42db-9992-de332c9df0e6"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"Quantization (signal) , Channel estimation , Symbols , OFDM , Estimation , Mutual information , Training, Physical layer secret key generation , orthogonal frequency-division multiplexing (OFDM) , channel estimation , neural network , mutual information","subitem_subject_language":"en","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"journal article","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"A Data-Driven Analysis of Secret Key Rate for Physical Layer Secret Key Generation from Wireless Channels","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"A Data-Driven Analysis of Secret Key Rate for Physical Layer Secret Key Generation from Wireless Channels","subitem_title_language":"en"}]},"item_type_id":"2","owner":"17","path":["1009"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2023-10-19"},"publish_date":"2023-10-19","publish_status":"0","recid":"2000106","relation_version_is_last":true,"title":["A Data-Driven Analysis of Secret Key Rate for Physical Layer Secret Key Generation from Wireless Channels"],"weko_creator_id":"17","weko_shared_id":-1},"updated":"2024-06-20T02:37:25.340726+00:00"}