{"title":"基于半定松弛的组播发射波束形成的逼近界","authors":"Tsung-Hui Chang, Z. Luo, Chong-Yung Chi","doi":"10.1109/CAMSAP.2007.4497998","DOIUrl":null,"url":null,"abstract":"The max-min-fair transmit beamforming problem in multigroup broadcasting has been shown to be NP-hard in general. Recently, a polynomial time approximation approach based on semidefinite relaxation (SDR) has been proposed [1]. It was found [1], through computer simulations, that this method is capable of giving a good approximate solution in polynomial time. This paper shows that the SDR based approach can guarantee as least an 0(1/M) approximation quality, where M is the total number of receivers. The existence of such a data independent bound certifies the worst case approximation quality of the SDR algorithm for any problem instance and any number of transmit antennas.","PeriodicalId":220687,"journal":{"name":"2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing","volume":"29 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Approximation Bound for Semidefinite Relaxation Based Multicast Transmit Beamforming\",\"authors\":\"Tsung-Hui Chang, Z. Luo, Chong-Yung Chi\",\"doi\":\"10.1109/CAMSAP.2007.4497998\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The max-min-fair transmit beamforming problem in multigroup broadcasting has been shown to be NP-hard in general. Recently, a polynomial time approximation approach based on semidefinite relaxation (SDR) has been proposed [1]. It was found [1], through computer simulations, that this method is capable of giving a good approximate solution in polynomial time. This paper shows that the SDR based approach can guarantee as least an 0(1/M) approximation quality, where M is the total number of receivers. The existence of such a data independent bound certifies the worst case approximation quality of the SDR algorithm for any problem instance and any number of transmit antennas.\",\"PeriodicalId\":220687,\"journal\":{\"name\":\"2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing\",\"volume\":\"29 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CAMSAP.2007.4497998\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 2nd IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CAMSAP.2007.4497998","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Approximation Bound for Semidefinite Relaxation Based Multicast Transmit Beamforming
The max-min-fair transmit beamforming problem in multigroup broadcasting has been shown to be NP-hard in general. Recently, a polynomial time approximation approach based on semidefinite relaxation (SDR) has been proposed [1]. It was found [1], through computer simulations, that this method is capable of giving a good approximate solution in polynomial time. This paper shows that the SDR based approach can guarantee as least an 0(1/M) approximation quality, where M is the total number of receivers. The existence of such a data independent bound certifies the worst case approximation quality of the SDR algorithm for any problem instance and any number of transmit antennas.