{"title":"noma辅助移动边缘计算的能耗最小化","authors":"Hao Xu, Yao Zhu, Kai Xiang, Yulin Hu, A. Schmeink","doi":"10.1109/ISWCS56560.2022.9940422","DOIUrl":null,"url":null,"abstract":"In this paper, we investigate a non-orthogonal multiple access (NOMA)-assisted mobile edge computing (MEC) network supporting a time-sensitive computing task with data inputs being generated at and offloaded from multiple users. To minimize the energy consumption of both users and server, a joint power and computational resource allocation problem is formulated, which is unfortunately non-convex. To address the problem and obtain the global optimal solution, we first carefully characterize optimality conditions of the problem, and then provide an efficient approach to transform the problem to an equivalent convex one. Via numerical simulation, our analytical results are validated and the impacts of channel quality, task deadline and computation workload on the system performance are investigated and evaluated.","PeriodicalId":141258,"journal":{"name":"2022 International Symposium on Wireless Communication Systems (ISWCS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Energy Consumption Minimization for NOMA-Assisted Mobile Edge Computing\",\"authors\":\"Hao Xu, Yao Zhu, Kai Xiang, Yulin Hu, A. Schmeink\",\"doi\":\"10.1109/ISWCS56560.2022.9940422\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we investigate a non-orthogonal multiple access (NOMA)-assisted mobile edge computing (MEC) network supporting a time-sensitive computing task with data inputs being generated at and offloaded from multiple users. To minimize the energy consumption of both users and server, a joint power and computational resource allocation problem is formulated, which is unfortunately non-convex. To address the problem and obtain the global optimal solution, we first carefully characterize optimality conditions of the problem, and then provide an efficient approach to transform the problem to an equivalent convex one. Via numerical simulation, our analytical results are validated and the impacts of channel quality, task deadline and computation workload on the system performance are investigated and evaluated.\",\"PeriodicalId\":141258,\"journal\":{\"name\":\"2022 International Symposium on Wireless Communication Systems (ISWCS)\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Symposium on Wireless Communication Systems (ISWCS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISWCS56560.2022.9940422\",\"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 International Symposium on Wireless Communication Systems (ISWCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISWCS56560.2022.9940422","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Energy Consumption Minimization for NOMA-Assisted Mobile Edge Computing
In this paper, we investigate a non-orthogonal multiple access (NOMA)-assisted mobile edge computing (MEC) network supporting a time-sensitive computing task with data inputs being generated at and offloaded from multiple users. To minimize the energy consumption of both users and server, a joint power and computational resource allocation problem is formulated, which is unfortunately non-convex. To address the problem and obtain the global optimal solution, we first carefully characterize optimality conditions of the problem, and then provide an efficient approach to transform the problem to an equivalent convex one. Via numerical simulation, our analytical results are validated and the impacts of channel quality, task deadline and computation workload on the system performance are investigated and evaluated.