{"title":"高斯多对一干扰网络的最优传输策略","authors":"Ranga Prasad, S. Bhashyam, A. Chockalingam","doi":"10.1109/ICC.2014.6883609","DOIUrl":null,"url":null,"abstract":"We study the Gaussian many-to-one interference network which is a special case of general interference network, where only one receiver experiences interference. We allow transmission of messages on all the links of the network. This communication model is different from the corresponding many-to-one interference channel. We formulate three transmission strategies for the above network, which involve using Gaussian codebooks and treating interference from a subset of the transmitters as noise. We use sum-rate as the criterion of optimality for evaluating the strategies. For the first two strategies, we characterize the sum-rate capacity under certain channel conditions, while for the other strategy, we derive a sum-rate outer bound and characterize the gap between the outer bound and the achievable sum-rate of the strategy. Finally, we illustrate the regions where the derived channel conditions are satisfied for each strategy.","PeriodicalId":444628,"journal":{"name":"2014 IEEE International Conference on Communications (ICC)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Optimum transmission strategies for the Gaussian many-to-one interference network\",\"authors\":\"Ranga Prasad, S. Bhashyam, A. Chockalingam\",\"doi\":\"10.1109/ICC.2014.6883609\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We study the Gaussian many-to-one interference network which is a special case of general interference network, where only one receiver experiences interference. We allow transmission of messages on all the links of the network. This communication model is different from the corresponding many-to-one interference channel. We formulate three transmission strategies for the above network, which involve using Gaussian codebooks and treating interference from a subset of the transmitters as noise. We use sum-rate as the criterion of optimality for evaluating the strategies. For the first two strategies, we characterize the sum-rate capacity under certain channel conditions, while for the other strategy, we derive a sum-rate outer bound and characterize the gap between the outer bound and the achievable sum-rate of the strategy. Finally, we illustrate the regions where the derived channel conditions are satisfied for each strategy.\",\"PeriodicalId\":444628,\"journal\":{\"name\":\"2014 IEEE International Conference on Communications (ICC)\",\"volume\":\"71 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-06-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 IEEE International Conference on Communications (ICC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICC.2014.6883609\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE International Conference on Communications (ICC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICC.2014.6883609","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimum transmission strategies for the Gaussian many-to-one interference network
We study the Gaussian many-to-one interference network which is a special case of general interference network, where only one receiver experiences interference. We allow transmission of messages on all the links of the network. This communication model is different from the corresponding many-to-one interference channel. We formulate three transmission strategies for the above network, which involve using Gaussian codebooks and treating interference from a subset of the transmitters as noise. We use sum-rate as the criterion of optimality for evaluating the strategies. For the first two strategies, we characterize the sum-rate capacity under certain channel conditions, while for the other strategy, we derive a sum-rate outer bound and characterize the gap between the outer bound and the achievable sum-rate of the strategy. Finally, we illustrate the regions where the derived channel conditions are satisfied for each strategy.