{"title":"CDMA Receiver Using Neural Network","authors":"S. Kanotai, Y. Rangsanseri","doi":"10.1109/APCC.2006.255807","DOIUrl":null,"url":null,"abstract":"This research presents a new structure of neural network based direct sequence code division multiple access (DS-CDMA) receiver. In CDMA system, near-far problem is a major impediment for the performance of conventional detector. In this paper we propose a back-propagation neural network (BPNN) based method that has the capability to combat the near-far and multiple user interference (MUI) problems. A comparative study between the conventional match filter and the neural network receiver is carried out using numerical method simulation. It was found that the proposed neural network receiver outperform the conventional receiver","PeriodicalId":205758,"journal":{"name":"2006 Asia-Pacific Conference on Communications","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2006 Asia-Pacific Conference on Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APCC.2006.255807","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This research presents a new structure of neural network based direct sequence code division multiple access (DS-CDMA) receiver. In CDMA system, near-far problem is a major impediment for the performance of conventional detector. In this paper we propose a back-propagation neural network (BPNN) based method that has the capability to combat the near-far and multiple user interference (MUI) problems. A comparative study between the conventional match filter and the neural network receiver is carried out using numerical method simulation. It was found that the proposed neural network receiver outperform the conventional receiver