{"title":"不完全功率控制下DS PPM超宽带多址系统的精确误码率分析","authors":"Wei Cao, A. Nallanathan, B. Kannan, C. C. Chai","doi":"10.1109/MILCOM.2005.1605806","DOIUrl":null,"url":null,"abstract":"Bit error rate (BER) performance of various UWB systems has been analyzed in numerous literatures. Most of the BER evaluation in these publications is based on some approximations. In this paper, we propose a method based on characteristic function (CF) to derive exact BER of DS UWB systems using pulse position modulation (PPM) under imperfect power control. In contrast to the widely used Gaussian approximation (GA) method, CF method deals with the exact distribution of total noise (including multiple-access interference and AWGN noise) other than making any assumptions on the distribution of total noise. Therefore CF method offers much more accurate BER prediction than GA method does. Our analytical derivations are validated by simulation results","PeriodicalId":223742,"journal":{"name":"MILCOM 2005 - 2005 IEEE Military Communications Conference","volume":"38 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Exact BER analysis of DS PPM UWB multiple access system under imperfect power control\",\"authors\":\"Wei Cao, A. Nallanathan, B. Kannan, C. C. Chai\",\"doi\":\"10.1109/MILCOM.2005.1605806\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Bit error rate (BER) performance of various UWB systems has been analyzed in numerous literatures. Most of the BER evaluation in these publications is based on some approximations. In this paper, we propose a method based on characteristic function (CF) to derive exact BER of DS UWB systems using pulse position modulation (PPM) under imperfect power control. In contrast to the widely used Gaussian approximation (GA) method, CF method deals with the exact distribution of total noise (including multiple-access interference and AWGN noise) other than making any assumptions on the distribution of total noise. Therefore CF method offers much more accurate BER prediction than GA method does. Our analytical derivations are validated by simulation results\",\"PeriodicalId\":223742,\"journal\":{\"name\":\"MILCOM 2005 - 2005 IEEE Military Communications Conference\",\"volume\":\"38 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-10-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"MILCOM 2005 - 2005 IEEE Military Communications Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MILCOM.2005.1605806\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"MILCOM 2005 - 2005 IEEE Military Communications Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MILCOM.2005.1605806","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Exact BER analysis of DS PPM UWB multiple access system under imperfect power control
Bit error rate (BER) performance of various UWB systems has been analyzed in numerous literatures. Most of the BER evaluation in these publications is based on some approximations. In this paper, we propose a method based on characteristic function (CF) to derive exact BER of DS UWB systems using pulse position modulation (PPM) under imperfect power control. In contrast to the widely used Gaussian approximation (GA) method, CF method deals with the exact distribution of total noise (including multiple-access interference and AWGN noise) other than making any assumptions on the distribution of total noise. Therefore CF method offers much more accurate BER prediction than GA method does. Our analytical derivations are validated by simulation results