Trimeche Abdessalem, Boukid Nesrine, A. Sakly, A. Mtibaa
{"title":"Performance analysis of ZF and MMSE equalizers for MIMO systems","authors":"Trimeche Abdessalem, Boukid Nesrine, A. Sakly, A. Mtibaa","doi":"10.1109/DTIS.2012.6232979","DOIUrl":null,"url":null,"abstract":"This paper presents an in-depth analysis of the zero forcing (ZF) and minimum mean squared error (MMSE) equalizers applied to wireless multi-input multi-output (MIMO) systems with no fewer receive than transmit antennas. In spite of much prior work on this subject, we reveal several new and surprising analytical results in terms of output signal-to-noise ratio (SNR), by comparing the Bit Error Rate (BER) and the average detection time consuming. Simulation based on the platform of MATLAB. We discuss the case where there a multiple transmit antennas and multiple receive antennas resulting in the formation of a Multiple Input Multiple Output (MIMO) channel with Zero Forcing equalizer, MIMO with MMSE equalizer, MIMO with ZF Successive Interference Cancellation equalizer, MIMO with ML equalization, MIMO with MMSE SIC and optimal ordering.","PeriodicalId":114829,"journal":{"name":"7th International Conference on Design & Technology of Integrated Systems in Nanoscale Era","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"32","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"7th International Conference on Design & Technology of Integrated Systems in Nanoscale Era","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DTIS.2012.6232979","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 32
Abstract
This paper presents an in-depth analysis of the zero forcing (ZF) and minimum mean squared error (MMSE) equalizers applied to wireless multi-input multi-output (MIMO) systems with no fewer receive than transmit antennas. In spite of much prior work on this subject, we reveal several new and surprising analytical results in terms of output signal-to-noise ratio (SNR), by comparing the Bit Error Rate (BER) and the average detection time consuming. Simulation based on the platform of MATLAB. We discuss the case where there a multiple transmit antennas and multiple receive antennas resulting in the formation of a Multiple Input Multiple Output (MIMO) channel with Zero Forcing equalizer, MIMO with MMSE equalizer, MIMO with ZF Successive Interference Cancellation equalizer, MIMO with ML equalization, MIMO with MMSE SIC and optimal ordering.