{"title":"C-RAN中效用最大化的前传压缩与传输策略研究","authors":"Zhenjun Dong, Jian Zhao","doi":"10.1109/ICTC.2018.8539348","DOIUrl":null,"url":null,"abstract":"Utility maximization is a fundamental problem in cellular network optimization. This paper considers joint optimization of data compression and downlink transmission strategies in a cloud radio access network (C-RAN) with finite fronthaul capacity. Our aim is to maximize the system utility with given quality of service (QoS) requirements for the users in such a network. We propose to exploit the optimality conditions and design a low-complexity iterative algorithm to obtain local optimal solutions. Compared with standard interior-point algorithms, simulations show that the proposed algorithm can reduce the processing time to as low as 1/625 while achieving the same final results. Comparisons with other transmission strategies are performed using numerical simulations.","PeriodicalId":417962,"journal":{"name":"2018 International Conference on Information and Communication Technology Convergence (ICTC)","volume":"191 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"On Fronthaul Compression and Transmission Strategies for Utility Maximization in C-RAN\",\"authors\":\"Zhenjun Dong, Jian Zhao\",\"doi\":\"10.1109/ICTC.2018.8539348\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Utility maximization is a fundamental problem in cellular network optimization. This paper considers joint optimization of data compression and downlink transmission strategies in a cloud radio access network (C-RAN) with finite fronthaul capacity. Our aim is to maximize the system utility with given quality of service (QoS) requirements for the users in such a network. We propose to exploit the optimality conditions and design a low-complexity iterative algorithm to obtain local optimal solutions. Compared with standard interior-point algorithms, simulations show that the proposed algorithm can reduce the processing time to as low as 1/625 while achieving the same final results. Comparisons with other transmission strategies are performed using numerical simulations.\",\"PeriodicalId\":417962,\"journal\":{\"name\":\"2018 International Conference on Information and Communication Technology Convergence (ICTC)\",\"volume\":\"191 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 International Conference on Information and Communication Technology Convergence (ICTC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICTC.2018.8539348\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 International Conference on Information and Communication Technology Convergence (ICTC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICTC.2018.8539348","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On Fronthaul Compression and Transmission Strategies for Utility Maximization in C-RAN
Utility maximization is a fundamental problem in cellular network optimization. This paper considers joint optimization of data compression and downlink transmission strategies in a cloud radio access network (C-RAN) with finite fronthaul capacity. Our aim is to maximize the system utility with given quality of service (QoS) requirements for the users in such a network. We propose to exploit the optimality conditions and design a low-complexity iterative algorithm to obtain local optimal solutions. Compared with standard interior-point algorithms, simulations show that the proposed algorithm can reduce the processing time to as low as 1/625 while achieving the same final results. Comparisons with other transmission strategies are performed using numerical simulations.