{"title":"Low-complexity dynamic spectrum management algorithms for digital subscriber lines","authors":"Paschalis Tsiaflakis, M. Moonen","doi":"10.1109/ICASSP.2008.4518223","DOIUrl":null,"url":null,"abstract":"Modern DSL networks suffer from crosstalk between different lines in the same cable bundle. By carefully choosing the transmit power spectra, the impact of crosstalk can be minimized leading to spectacular performance gains. This is also referred to as dynamic spectrum management (DSM). This paper presents three novel low-complexity DSM algorithms with a different level of required message-passing. This level ranges from fully autonomous and distributed to semi-centralized execution. Simulations show good performances compared to existing state-of-the-art DSM algorithms.","PeriodicalId":333742,"journal":{"name":"2008 IEEE International Conference on Acoustics, Speech and Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2008-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE International Conference on Acoustics, Speech and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASSP.2008.4518223","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
Modern DSL networks suffer from crosstalk between different lines in the same cable bundle. By carefully choosing the transmit power spectra, the impact of crosstalk can be minimized leading to spectacular performance gains. This is also referred to as dynamic spectrum management (DSM). This paper presents three novel low-complexity DSM algorithms with a different level of required message-passing. This level ranges from fully autonomous and distributed to semi-centralized execution. Simulations show good performances compared to existing state-of-the-art DSM algorithms.