{"title":"基于神经网络的扩频PN码采集系统","authors":"S. El-Khamy, E. Gelenbe, H. Abdelbaki","doi":"10.1109/NRSC.2000.838959","DOIUrl":null,"url":null,"abstract":"A neural network based direct sequence spread spectrum code synchronization system is proposed. The's system is based on training a recurrent random neural network (RNN) model on all the possible phases of the used spreading code. The trained network can then be used at the receiver for the initial coarse alignment of the local code phase and the received code. One advantage of this technique over the conventional synchronization techniques is that the phase of the received PN code can be decided without searching the potential code phases. Also the RNN, after being trained, can have a simple hardware realization that makes it candidate for implementation as a dedicated chip. This makes the neural network based technique faster and more robust than the conventional techniques. Computer simulations, carried out on maximal length sequences of length N=7 and N=15, show that the proposed system cast effectively indicate the phase of the received code even with very low signal to noise ratios.","PeriodicalId":211510,"journal":{"name":"Proceedings of the Seventeenth National Radio Science Conference. 17th NRSC'2000 (IEEE Cat. No.00EX396)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2000-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Neural network based spread spectrum PN code acquisition system\",\"authors\":\"S. El-Khamy, E. Gelenbe, H. Abdelbaki\",\"doi\":\"10.1109/NRSC.2000.838959\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A neural network based direct sequence spread spectrum code synchronization system is proposed. The's system is based on training a recurrent random neural network (RNN) model on all the possible phases of the used spreading code. The trained network can then be used at the receiver for the initial coarse alignment of the local code phase and the received code. One advantage of this technique over the conventional synchronization techniques is that the phase of the received PN code can be decided without searching the potential code phases. Also the RNN, after being trained, can have a simple hardware realization that makes it candidate for implementation as a dedicated chip. This makes the neural network based technique faster and more robust than the conventional techniques. Computer simulations, carried out on maximal length sequences of length N=7 and N=15, show that the proposed system cast effectively indicate the phase of the received code even with very low signal to noise ratios.\",\"PeriodicalId\":211510,\"journal\":{\"name\":\"Proceedings of the Seventeenth National Radio Science Conference. 17th NRSC'2000 (IEEE Cat. No.00EX396)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-02-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Seventeenth National Radio Science Conference. 17th NRSC'2000 (IEEE Cat. No.00EX396)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NRSC.2000.838959\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Seventeenth National Radio Science Conference. 17th NRSC'2000 (IEEE Cat. No.00EX396)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NRSC.2000.838959","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Neural network based spread spectrum PN code acquisition system
A neural network based direct sequence spread spectrum code synchronization system is proposed. The's system is based on training a recurrent random neural network (RNN) model on all the possible phases of the used spreading code. The trained network can then be used at the receiver for the initial coarse alignment of the local code phase and the received code. One advantage of this technique over the conventional synchronization techniques is that the phase of the received PN code can be decided without searching the potential code phases. Also the RNN, after being trained, can have a simple hardware realization that makes it candidate for implementation as a dedicated chip. This makes the neural network based technique faster and more robust than the conventional techniques. Computer simulations, carried out on maximal length sequences of length N=7 and N=15, show that the proposed system cast effectively indicate the phase of the received code even with very low signal to noise ratios.