Shivang Aggarwal, R. Sheshadri, K. Sundaresan, Dimitrios Koutsonikolas
{"title":"wifi 802.11mc精细时间测量为黄金时段定位做好准备了吗?","authors":"Shivang Aggarwal, R. Sheshadri, K. Sundaresan, Dimitrios Koutsonikolas","doi":"10.1145/3556564.3558234","DOIUrl":null,"url":null,"abstract":"WiFi's fine time measurement (FTM) based ranging protocol has set the stage for mass adoption of location-aware applications and services in WiFi-pervading enterprise and consumer ecosystems. However, the lack of deployment of such commercial-scale localization solutions has motivated us to conduct a comprehensive experimental study that aims to verify whether WiFi's FTM is indeed ready for prime-time localization. With heterogeneity in operation (devices, environments, and spectrum) being the fundamental essence of commercial deployments, our study focuses on FTM's ability to deliver useable localization under such practical conditions. Being a first of its kind, our study reveals several interesting insights for practical operation of FTM, with the most critical of them being its inability to eliminate substantial offsets in estimated ranges between heterogeneous devices and configurations that degrade performance significantly (up to 20 m error). Albeit a negative result for FTM's readiness, we also propose a simple but promising remedy - an over-the-top auto-calibration solution that allows every WiFi device, when it enters an enterprise environment, to self-calibrate its offsets on-demand, thereby salvaging FTM to render it useful (median error of 2 m) for localization.","PeriodicalId":140152,"journal":{"name":"Proceedings of the 16th ACM Workshop on Wireless Network Testbeds, Experimental evaluation & CHaracterization","volume":"49 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Is wifi 802.11mc fine time measurement ready for prime-time localization?\",\"authors\":\"Shivang Aggarwal, R. Sheshadri, K. Sundaresan, Dimitrios Koutsonikolas\",\"doi\":\"10.1145/3556564.3558234\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"WiFi's fine time measurement (FTM) based ranging protocol has set the stage for mass adoption of location-aware applications and services in WiFi-pervading enterprise and consumer ecosystems. However, the lack of deployment of such commercial-scale localization solutions has motivated us to conduct a comprehensive experimental study that aims to verify whether WiFi's FTM is indeed ready for prime-time localization. With heterogeneity in operation (devices, environments, and spectrum) being the fundamental essence of commercial deployments, our study focuses on FTM's ability to deliver useable localization under such practical conditions. Being a first of its kind, our study reveals several interesting insights for practical operation of FTM, with the most critical of them being its inability to eliminate substantial offsets in estimated ranges between heterogeneous devices and configurations that degrade performance significantly (up to 20 m error). Albeit a negative result for FTM's readiness, we also propose a simple but promising remedy - an over-the-top auto-calibration solution that allows every WiFi device, when it enters an enterprise environment, to self-calibrate its offsets on-demand, thereby salvaging FTM to render it useful (median error of 2 m) for localization.\",\"PeriodicalId\":140152,\"journal\":{\"name\":\"Proceedings of the 16th ACM Workshop on Wireless Network Testbeds, Experimental evaluation & CHaracterization\",\"volume\":\"49 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 16th ACM Workshop on Wireless Network Testbeds, Experimental evaluation & CHaracterization\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3556564.3558234\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 16th ACM Workshop on Wireless Network Testbeds, Experimental evaluation & CHaracterization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3556564.3558234","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Is wifi 802.11mc fine time measurement ready for prime-time localization?
WiFi's fine time measurement (FTM) based ranging protocol has set the stage for mass adoption of location-aware applications and services in WiFi-pervading enterprise and consumer ecosystems. However, the lack of deployment of such commercial-scale localization solutions has motivated us to conduct a comprehensive experimental study that aims to verify whether WiFi's FTM is indeed ready for prime-time localization. With heterogeneity in operation (devices, environments, and spectrum) being the fundamental essence of commercial deployments, our study focuses on FTM's ability to deliver useable localization under such practical conditions. Being a first of its kind, our study reveals several interesting insights for practical operation of FTM, with the most critical of them being its inability to eliminate substantial offsets in estimated ranges between heterogeneous devices and configurations that degrade performance significantly (up to 20 m error). Albeit a negative result for FTM's readiness, we also propose a simple but promising remedy - an over-the-top auto-calibration solution that allows every WiFi device, when it enters an enterprise environment, to self-calibrate its offsets on-demand, thereby salvaging FTM to render it useful (median error of 2 m) for localization.