{"title":"频谱效率CPM:次优的基于fg的多用户检测","authors":"N. Noels, M. Moeneclaey","doi":"10.1109/WCNC.2012.6214503","DOIUrl":null,"url":null,"abstract":"This paper presents a new iterative multiuser (MU) detection algorithm for asynchronous spectrally-efficient continuous-phase modulation in additive white Gaussian noise. The proposed detector is derived from the sum-product (SP) algorithm and the factor graph (FG) framework, and performs approximate maximum a posteriori bit detection. A convenient FG of the actual MU detection problem is considered, rather than only FGs of the individual single-user detection problems combined with ad-hoc inter-user interference cancellation. A suitable set of SP messages is approximated by a Gaussian distribution; this considerably reduces the computational complexity and memory size requirements as compared to a straightforward application of the SP rules. The resulting algorithm succeeds in achieving a good error performance.","PeriodicalId":329194,"journal":{"name":"2012 IEEE Wireless Communications and Networking Conference (WCNC)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Spectrally efficient CPM: Suboptimal FG-based multiuser detection\",\"authors\":\"N. Noels, M. Moeneclaey\",\"doi\":\"10.1109/WCNC.2012.6214503\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a new iterative multiuser (MU) detection algorithm for asynchronous spectrally-efficient continuous-phase modulation in additive white Gaussian noise. The proposed detector is derived from the sum-product (SP) algorithm and the factor graph (FG) framework, and performs approximate maximum a posteriori bit detection. A convenient FG of the actual MU detection problem is considered, rather than only FGs of the individual single-user detection problems combined with ad-hoc inter-user interference cancellation. A suitable set of SP messages is approximated by a Gaussian distribution; this considerably reduces the computational complexity and memory size requirements as compared to a straightforward application of the SP rules. The resulting algorithm succeeds in achieving a good error performance.\",\"PeriodicalId\":329194,\"journal\":{\"name\":\"2012 IEEE Wireless Communications and Networking Conference (WCNC)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE Wireless Communications and Networking Conference (WCNC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WCNC.2012.6214503\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE Wireless Communications and Networking Conference (WCNC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCNC.2012.6214503","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper presents a new iterative multiuser (MU) detection algorithm for asynchronous spectrally-efficient continuous-phase modulation in additive white Gaussian noise. The proposed detector is derived from the sum-product (SP) algorithm and the factor graph (FG) framework, and performs approximate maximum a posteriori bit detection. A convenient FG of the actual MU detection problem is considered, rather than only FGs of the individual single-user detection problems combined with ad-hoc inter-user interference cancellation. A suitable set of SP messages is approximated by a Gaussian distribution; this considerably reduces the computational complexity and memory size requirements as compared to a straightforward application of the SP rules. The resulting algorithm succeeds in achieving a good error performance.