{"title":"随机索引分配广播信道的最优多分辨率量化","authors":"Fei Teng, E. Yang, Xiang Yu","doi":"10.1109/ISIT.2010.5513257","DOIUrl":null,"url":null,"abstract":"This paper studies the design and analysis of multiresolution vector quantization (MRVQ) for broadcast channels. Given a broadcast system with MRVQ, a random index assignment, and a coded broadcast channel, we first obtain a closed-form formula for the weighted end-to-end distortion (EED) of the system. Based on the formula, an iterative algorithm is then proposed for designing optimal MRVQ for the broadcast system. Experimental results demonstrate that multiresolution quantizers jointly designed with channel conditions by the proposed algorithm significantly reduce the weighted EED in comparison with multiresolution quantizers designed without reference to channel conditions.","PeriodicalId":147055,"journal":{"name":"2010 IEEE International Symposium on Information Theory","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Optimal multiresolution quantization for broadcast channels with random index assignment\",\"authors\":\"Fei Teng, E. Yang, Xiang Yu\",\"doi\":\"10.1109/ISIT.2010.5513257\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper studies the design and analysis of multiresolution vector quantization (MRVQ) for broadcast channels. Given a broadcast system with MRVQ, a random index assignment, and a coded broadcast channel, we first obtain a closed-form formula for the weighted end-to-end distortion (EED) of the system. Based on the formula, an iterative algorithm is then proposed for designing optimal MRVQ for the broadcast system. Experimental results demonstrate that multiresolution quantizers jointly designed with channel conditions by the proposed algorithm significantly reduce the weighted EED in comparison with multiresolution quantizers designed without reference to channel conditions.\",\"PeriodicalId\":147055,\"journal\":{\"name\":\"2010 IEEE International Symposium on Information Theory\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-06-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE International Symposium on Information Theory\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISIT.2010.5513257\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Symposium on Information Theory","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISIT.2010.5513257","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimal multiresolution quantization for broadcast channels with random index assignment
This paper studies the design and analysis of multiresolution vector quantization (MRVQ) for broadcast channels. Given a broadcast system with MRVQ, a random index assignment, and a coded broadcast channel, we first obtain a closed-form formula for the weighted end-to-end distortion (EED) of the system. Based on the formula, an iterative algorithm is then proposed for designing optimal MRVQ for the broadcast system. Experimental results demonstrate that multiresolution quantizers jointly designed with channel conditions by the proposed algorithm significantly reduce the weighted EED in comparison with multiresolution quantizers designed without reference to channel conditions.