{"title":"Performance Analysis of Polynomial Matrix SVD-Based Broadband MIMO Systems","authors":"André Sandmann, A. Ahrens, S. Lochmann","doi":"10.1109/SSPD.2015.7288517","DOIUrl":null,"url":null,"abstract":"Singular-value decomposition (SVD) is well-established in multiple-input multiple-output (MIMO) signal processing where a broadband MIMO channel is transformed into a number of weighted single-input single-output (SISO) channels. However, applying SVD to frequency-selective MIMO channels results in unequally weighted SISO channels requiring complex resource allocation techniques for optimizing the channel performance. Therefore, a different approach utilizing polynomial matrix singular-value decomposition (PMSVD) for removing the MIMO interference is studied, outperforming conventional SVD-based MIMO systems in the analyzed channel scenarios. As shown by the bit-error rate (BER) simulation results as well as the obtained spectral efficiencies, the proposed PMSVD-based solution seems to be a good alternative to conventional SVD-based MIMO systems.","PeriodicalId":212668,"journal":{"name":"2015 Sensor Signal Processing for Defence (SSPD)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Sensor Signal Processing for Defence (SSPD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SSPD.2015.7288517","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Singular-value decomposition (SVD) is well-established in multiple-input multiple-output (MIMO) signal processing where a broadband MIMO channel is transformed into a number of weighted single-input single-output (SISO) channels. However, applying SVD to frequency-selective MIMO channels results in unequally weighted SISO channels requiring complex resource allocation techniques for optimizing the channel performance. Therefore, a different approach utilizing polynomial matrix singular-value decomposition (PMSVD) for removing the MIMO interference is studied, outperforming conventional SVD-based MIMO systems in the analyzed channel scenarios. As shown by the bit-error rate (BER) simulation results as well as the obtained spectral efficiencies, the proposed PMSVD-based solution seems to be a good alternative to conventional SVD-based MIMO systems.