{"title":"GMSK neural network based demodulator","authors":"A. Aiello, D. Grimaldi, S. Rapuano","doi":"10.1109/IDAACS.2001.941967","DOIUrl":null,"url":null,"abstract":"The pattern recognition characteristics of the Artificial Neural Networks are used to realise a real demodulator for Gaussian Minimum Shift-Keying signals, used in the GSM telecommunications. The demodulator utilizes the learning vector quantization (LVQ) neural network. It offers both greater efficiency in demodulating and less sensitivity to noise. In order to solve the problem regarding input signal synchronization, a pre-processing phase is organised. The demodulator prototype has been realised by implementing the pre-processing phase and the LVQ neural network on TMS320C30 digital signal processor. The demodulator has been tested according to the European Telecommunication Standard Institute recommendations.","PeriodicalId":419022,"journal":{"name":"Proceedings of the International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications. IDAACS'2001 (Cat. No.01EX510)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications. IDAACS'2001 (Cat. No.01EX510)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IDAACS.2001.941967","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
Abstract
The pattern recognition characteristics of the Artificial Neural Networks are used to realise a real demodulator for Gaussian Minimum Shift-Keying signals, used in the GSM telecommunications. The demodulator utilizes the learning vector quantization (LVQ) neural network. It offers both greater efficiency in demodulating and less sensitivity to noise. In order to solve the problem regarding input signal synchronization, a pre-processing phase is organised. The demodulator prototype has been realised by implementing the pre-processing phase and the LVQ neural network on TMS320C30 digital signal processor. The demodulator has been tested according to the European Telecommunication Standard Institute recommendations.
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