{"title":"基于候选列表的近最优矢量扰动预编码","authors":"Henning Vetter, V. Ponnampalam","doi":"10.1109/WCNC.2009.4917825","DOIUrl":null,"url":null,"abstract":"An improvement to lattice-reduction-aided (LRA) vector perturbation precoding for multi-user MIMO downlink is introduced. Closest lattice point approximation by means of lattice reduction techniques can significantly lower the complexity of the closest point search compared to using a sphere encoder, but the performance of the system is also impaired. In this paper, we propose a new technique improving the suboptimal LRA closest-point approximation in a subsequent stage. This stage consists of a low-complexity candidate list generation of also likely approximations, and an evaluation step of this list. We present simulation results showing that our improvement to the LRA closest-point approximation can achieve near-optimum performance.","PeriodicalId":186150,"journal":{"name":"2009 IEEE Wireless Communications and Networking Conference","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Near-Optimum Vector Perturbation Precoding Using a Candidate List\",\"authors\":\"Henning Vetter, V. Ponnampalam\",\"doi\":\"10.1109/WCNC.2009.4917825\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An improvement to lattice-reduction-aided (LRA) vector perturbation precoding for multi-user MIMO downlink is introduced. Closest lattice point approximation by means of lattice reduction techniques can significantly lower the complexity of the closest point search compared to using a sphere encoder, but the performance of the system is also impaired. In this paper, we propose a new technique improving the suboptimal LRA closest-point approximation in a subsequent stage. This stage consists of a low-complexity candidate list generation of also likely approximations, and an evaluation step of this list. We present simulation results showing that our improvement to the LRA closest-point approximation can achieve near-optimum performance.\",\"PeriodicalId\":186150,\"journal\":{\"name\":\"2009 IEEE Wireless Communications and Networking Conference\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-04-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE Wireless Communications and Networking Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WCNC.2009.4917825\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE Wireless Communications and Networking Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WCNC.2009.4917825","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Near-Optimum Vector Perturbation Precoding Using a Candidate List
An improvement to lattice-reduction-aided (LRA) vector perturbation precoding for multi-user MIMO downlink is introduced. Closest lattice point approximation by means of lattice reduction techniques can significantly lower the complexity of the closest point search compared to using a sphere encoder, but the performance of the system is also impaired. In this paper, we propose a new technique improving the suboptimal LRA closest-point approximation in a subsequent stage. This stage consists of a low-complexity candidate list generation of also likely approximations, and an evaluation step of this list. We present simulation results showing that our improvement to the LRA closest-point approximation can achieve near-optimum performance.