{"title":"基于人工智能的IEEE 802.11切换策略仿真","authors":"Alexander Brezáni, Rastislav Bencel","doi":"10.1109/ICETA57911.2022.9974643","DOIUrl":null,"url":null,"abstract":"Nowadays, standard IEEE 802.11 is widely used and, with the correct approach, can be used to cover a large area. It can be used in cities within the intelligent infrastructure. In this usage, there is essential to have an effective handover and its strategies. This paper focuses on handover strategies in standard IEEE 802.11. The article briefly describes existing handover strategies and introduces a new one based on AI, which is evaluated in our simulation tool implemented in Matlab. The Simulator can be used to model a specific environment, including obstacles that are important to achieve constrain of the real environment. The contribution of this simulation tool is focusing on handover strategies and avoiding the infrastructure layer, which is the next step after finding a good handover strategy. The presented new handover strategy is based on reinforcement learning and achieves better results than the standard strategies described in this paper.","PeriodicalId":151344,"journal":{"name":"2022 20th International Conference on Emerging eLearning Technologies and Applications (ICETA)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Handover strategies simulations in IEEE 802.11 based on Artificial Intelligence\",\"authors\":\"Alexander Brezáni, Rastislav Bencel\",\"doi\":\"10.1109/ICETA57911.2022.9974643\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Nowadays, standard IEEE 802.11 is widely used and, with the correct approach, can be used to cover a large area. It can be used in cities within the intelligent infrastructure. In this usage, there is essential to have an effective handover and its strategies. This paper focuses on handover strategies in standard IEEE 802.11. The article briefly describes existing handover strategies and introduces a new one based on AI, which is evaluated in our simulation tool implemented in Matlab. The Simulator can be used to model a specific environment, including obstacles that are important to achieve constrain of the real environment. The contribution of this simulation tool is focusing on handover strategies and avoiding the infrastructure layer, which is the next step after finding a good handover strategy. The presented new handover strategy is based on reinforcement learning and achieves better results than the standard strategies described in this paper.\",\"PeriodicalId\":151344,\"journal\":{\"name\":\"2022 20th International Conference on Emerging eLearning Technologies and Applications (ICETA)\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 20th International Conference on Emerging eLearning Technologies and Applications (ICETA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICETA57911.2022.9974643\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 20th International Conference on Emerging eLearning Technologies and Applications (ICETA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICETA57911.2022.9974643","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Handover strategies simulations in IEEE 802.11 based on Artificial Intelligence
Nowadays, standard IEEE 802.11 is widely used and, with the correct approach, can be used to cover a large area. It can be used in cities within the intelligent infrastructure. In this usage, there is essential to have an effective handover and its strategies. This paper focuses on handover strategies in standard IEEE 802.11. The article briefly describes existing handover strategies and introduces a new one based on AI, which is evaluated in our simulation tool implemented in Matlab. The Simulator can be used to model a specific environment, including obstacles that are important to achieve constrain of the real environment. The contribution of this simulation tool is focusing on handover strategies and avoiding the infrastructure layer, which is the next step after finding a good handover strategy. The presented new handover strategy is based on reinforcement learning and achieves better results than the standard strategies described in this paper.