{"updated":"2025-01-19T08:02:27.113447+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00240236","sets":["6164:6165:6640:11802"]},"path":["11802"],"owner":"44499","recid":"240236","title":["機械学習によるV2X向け動的ミリ波ビーム探索法"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-06-19"},"_buckets":{"deposit":"edf9597f-e916-4671-a4ec-45ae169e6fa8"},"_deposit":{"id":"240236","pid":{"type":"depid","value":"240236","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"機械学習によるV2X向け動的ミリ波ビーム探索法","author_link":["658774","658775","658773","658772","658771","658776"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"機械学習によるV2X向け動的ミリ波ビーム探索法"}]},"item_type_id":"18","publish_date":"2024-06-19","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_18_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"東京大学"},{"subitem_text_value":"東京大学"},{"subitem_text_value":"東京理科大学"},{"subitem_text_value":"東京大学"},{"subitem_text_value":"東京大学"},{"subitem_text_value":"東京大学"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/240236/files/IPSJ-DICOMO2024120.pdf","label":"IPSJ-DICOMO2024120.pdf"},"date":[{"dateType":"Available","dateValue":"2026-06-19"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-DICOMO2024120.pdf","filesize":[{"value":"3.4 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"e0bd909f-f05f-401e-9489-f888ccc4cba6","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"岩城, 燎"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"中里, 仁"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"丸田, 一輝"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"塚田, 学"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"落合, 秀也"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"江崎, 浩"}],"nameIdentifiers":[{}]}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_18_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"2019年より世界中でサービスが開始された5Gでは，ミリ波が移動体通信として初めて導入された．ミリ波は直進性が強く，回り込みしない特徴からカバレッジが小さいスモールセルへの導入がされている．一方で，様々な交通システムが協調的に認知，判断，実行を担える協調型自動運転では，通信に常時繋がることが前提とされている．高速移動する車両に対して，低遅延通信が可能なミリ波を用いるためには，5Gにおけるビームフォーミングでは高速で追従できないという課題がある．本研究では，自作のデータセットを用いて機械学習を行い，ビーム追従アルゴリズムの探索方式を道路状況にあわせて動的な切り替えができるようなアルゴリズムを実装した．既存の手法を単独で用いたときよりも，更に高い通信品質が確保できることをシミュレーションによって確かめた．これによって複雑な形状をした現実の道路でも最大限の性能を発揮することができるようになった．","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"882","bibliographic_titles":[{"bibliographic_title":"マルチメディア，分散，協調とモバイルシンポジウム2024論文集"}],"bibliographicPageStart":"876","bibliographicIssueDates":{"bibliographicIssueDate":"2024-06-19","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"2024"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T01:44:19.026397+00:00","id":240236,"links":{}}