{"title":"OPPORTUNISTIC SPECTRUM ACCESS VIA GOOD ARM IDENTIFICATION","authors":"Zhiyang Wang, Ziyu Ying, Cong Shen","doi":"10.1109/GlobalSIP.2018.8646686","DOIUrl":null,"url":null,"abstract":"In this work, we promote a different tool of multi-armed bandits (MAB), called arm identification, to choose a suitable channel for Opportunistic Spectrum Access (OSA) with proven accuracy while satisfying stringent constraints on delay, energy consumption, and channel switches. Noting that finding the best channel may not always be the optimal choice, we deviate from the celebrated best arm identification framework and adopt good arm identification (GAI), which results in a channel that is \"good enough\", but requires much less time and energy consumption under the same accuracy requirement. Robustness issues such as delayed or missing feedback are also studied under the new framework. Performance of the proposed algorithm is studied analytically and further corroborated via numerical simulations.","PeriodicalId":119131,"journal":{"name":"2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GlobalSIP.2018.8646686","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
In this work, we promote a different tool of multi-armed bandits (MAB), called arm identification, to choose a suitable channel for Opportunistic Spectrum Access (OSA) with proven accuracy while satisfying stringent constraints on delay, energy consumption, and channel switches. Noting that finding the best channel may not always be the optimal choice, we deviate from the celebrated best arm identification framework and adopt good arm identification (GAI), which results in a channel that is "good enough", but requires much less time and energy consumption under the same accuracy requirement. Robustness issues such as delayed or missing feedback are also studied under the new framework. Performance of the proposed algorithm is studied analytically and further corroborated via numerical simulations.