{"title":"低轨道卫星网络中基于延迟可调IRS的深度q -学习驱动频率棱镜波束形成","authors":"Shuta Sekimori, Hiroaki Hashida, Yuichi Kawamoto, Nei Kato, Kohei Yoshida, Masayuki Ariyoshi","doi":"10.1109/tccn.2025.3567094","DOIUrl":null,"url":null,"abstract":"","PeriodicalId":13069,"journal":{"name":"IEEE Transactions on Cognitive Communications and Networking","volume":"56 1","pages":"1-1"},"PeriodicalIF":7.4000,"publicationDate":"2025-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Deep Q-Learning-Driven Frequency Prism Beamforming With Delay-Adjustable IRS in LEO Satellite Networks\",\"authors\":\"Shuta Sekimori, Hiroaki Hashida, Yuichi Kawamoto, Nei Kato, Kohei Yoshida, Masayuki Ariyoshi\",\"doi\":\"10.1109/tccn.2025.3567094\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\",\"PeriodicalId\":13069,\"journal\":{\"name\":\"IEEE Transactions on Cognitive Communications and Networking\",\"volume\":\"56 1\",\"pages\":\"1-1\"},\"PeriodicalIF\":7.4000,\"publicationDate\":\"2025-05-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Cognitive Communications and Networking\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1109/tccn.2025.3567094\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"TELECOMMUNICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Cognitive Communications and Networking","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1109/tccn.2025.3567094","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"TELECOMMUNICATIONS","Score":null,"Total":0}
期刊介绍:
The IEEE Transactions on Cognitive Communications and Networking (TCCN) aims to publish high-quality manuscripts that push the boundaries of cognitive communications and networking research. Cognitive, in this context, refers to the application of perception, learning, reasoning, memory, and adaptive approaches in communication system design. The transactions welcome submissions that explore various aspects of cognitive communications and networks, focusing on innovative and holistic approaches to complex system design. Key topics covered include architecture, protocols, cross-layer design, and cognition cycle design for cognitive networks. Additionally, research on machine learning, artificial intelligence, end-to-end and distributed intelligence, software-defined networking, cognitive radios, spectrum sharing, and security and privacy issues in cognitive networks are of interest. The publication also encourages papers addressing novel services and applications enabled by these cognitive concepts.