{"title":"通过智能手机和CRFO教与学无线通信原理","authors":"P. Chandhar, S. Babu, T. Elakkiya","doi":"10.1109/ICETCI51973.2021.9574082","DOIUrl":null,"url":null,"abstract":"In this paper, we discuss the possibilities of teaching and learning the principles of wireless communications using smartphones and Collaborative Radio Frequency Observatory (CRFO), an online platform for maintaining RF datasets for Machine Learning related experiments. First, we present three simple smartphone based experiments for understanding the basic concepts of mobile communications such as pathloss, Shadow fading, and small scale fading. Then we explain the use of CRFO for visualizing radio coverage maps based on the measurements taken using smartphones. The results show that computationally efficient tools can be developed for teaching advanced wireless communication concepts.","PeriodicalId":281877,"journal":{"name":"2021 International Conference on Emerging Techniques in Computational Intelligence (ICETCI)","volume":"141 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Teaching and Learning the Principles of Wireless Communication through Smartphone and CRFO\",\"authors\":\"P. Chandhar, S. Babu, T. Elakkiya\",\"doi\":\"10.1109/ICETCI51973.2021.9574082\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we discuss the possibilities of teaching and learning the principles of wireless communications using smartphones and Collaborative Radio Frequency Observatory (CRFO), an online platform for maintaining RF datasets for Machine Learning related experiments. First, we present three simple smartphone based experiments for understanding the basic concepts of mobile communications such as pathloss, Shadow fading, and small scale fading. Then we explain the use of CRFO for visualizing radio coverage maps based on the measurements taken using smartphones. The results show that computationally efficient tools can be developed for teaching advanced wireless communication concepts.\",\"PeriodicalId\":281877,\"journal\":{\"name\":\"2021 International Conference on Emerging Techniques in Computational Intelligence (ICETCI)\",\"volume\":\"141 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-08-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 International Conference on Emerging Techniques in Computational Intelligence (ICETCI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICETCI51973.2021.9574082\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Emerging Techniques in Computational Intelligence (ICETCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICETCI51973.2021.9574082","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Teaching and Learning the Principles of Wireless Communication through Smartphone and CRFO
In this paper, we discuss the possibilities of teaching and learning the principles of wireless communications using smartphones and Collaborative Radio Frequency Observatory (CRFO), an online platform for maintaining RF datasets for Machine Learning related experiments. First, we present three simple smartphone based experiments for understanding the basic concepts of mobile communications such as pathloss, Shadow fading, and small scale fading. Then we explain the use of CRFO for visualizing radio coverage maps based on the measurements taken using smartphones. The results show that computationally efficient tools can be developed for teaching advanced wireless communication concepts.