{"title":"MDUcast:视频物联网中的多设备上行无编码视频传输","authors":"Qiaojia Lu, Hanchen Lu, Xinyu Yang, Feihong Chen","doi":"10.1109/WCNC55385.2023.10119011","DOIUrl":null,"url":null,"abstract":"With the widely deployed video sensors, Internet of Video Things (IoVT) has emerged as a new paradigm of Internet of Things (IoT). Due to limited computing capacity of video sensors and multi-device wireless environments in IoVT, uplink video transmission faces challenges brought by complex coding and heterogeneous channel conditions. To combat these challenges, we propose a multi-device uplink uncoded video transmission scheme (MDUcast). Different from traditional encoded video transmission systems, MDUcast performs efficient linear operations instead of complex coding to reduce computing requirements on video sensors as well as guarantee the reconstructed video quality proportional to channel conditions in heterogenous environments. Furthermore, in MDUcast, an optimal power allocation strategy and a subcarrier scheduling algorithm based on matching theory are proposed to approach the near-optimal performance for multi-device uplink transmission, where both channel diversity and video content diversity are exploited. Simulation results demonstrate that MDUcast outperforms conventional Softcast and Parcast in terms of peak signal-to-noise ratio under various scenarios.","PeriodicalId":259116,"journal":{"name":"2023 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"MDUcast: Multi-Device Uplink Uncoded Video Transmission in Internet of Video Things\",\"authors\":\"Qiaojia Lu, Hanchen Lu, Xinyu Yang, Feihong Chen\",\"doi\":\"10.1109/WCNC55385.2023.10119011\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the widely deployed video sensors, Internet of Video Things (IoVT) has emerged as a new paradigm of Internet of Things (IoT). Due to limited computing capacity of video sensors and multi-device wireless environments in IoVT, uplink video transmission faces challenges brought by complex coding and heterogeneous channel conditions. To combat these challenges, we propose a multi-device uplink uncoded video transmission scheme (MDUcast). Different from traditional encoded video transmission systems, MDUcast performs efficient linear operations instead of complex coding to reduce computing requirements on video sensors as well as guarantee the reconstructed video quality proportional to channel conditions in heterogenous environments. Furthermore, in MDUcast, an optimal power allocation strategy and a subcarrier scheduling algorithm based on matching theory are proposed to approach the near-optimal performance for multi-device uplink transmission, where both channel diversity and video content diversity are exploited. Simulation results demonstrate that MDUcast outperforms conventional Softcast and Parcast in terms of peak signal-to-noise ratio under various scenarios.\",\"PeriodicalId\":259116,\"journal\":{\"name\":\"2023 IEEE Wireless Communications and Networking Conference (WCNC)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IEEE Wireless Communications and Networking Conference (WCNC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WCNC55385.2023.10119011\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE Wireless Communications and Networking Conference (WCNC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCNC55385.2023.10119011","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
MDUcast: Multi-Device Uplink Uncoded Video Transmission in Internet of Video Things
With the widely deployed video sensors, Internet of Video Things (IoVT) has emerged as a new paradigm of Internet of Things (IoT). Due to limited computing capacity of video sensors and multi-device wireless environments in IoVT, uplink video transmission faces challenges brought by complex coding and heterogeneous channel conditions. To combat these challenges, we propose a multi-device uplink uncoded video transmission scheme (MDUcast). Different from traditional encoded video transmission systems, MDUcast performs efficient linear operations instead of complex coding to reduce computing requirements on video sensors as well as guarantee the reconstructed video quality proportional to channel conditions in heterogenous environments. Furthermore, in MDUcast, an optimal power allocation strategy and a subcarrier scheduling algorithm based on matching theory are proposed to approach the near-optimal performance for multi-device uplink transmission, where both channel diversity and video content diversity are exploited. Simulation results demonstrate that MDUcast outperforms conventional Softcast and Parcast in terms of peak signal-to-noise ratio under various scenarios.