Blind SNR estimation based on cyclostationarity
Upsampling and shaping filtering introduce the cyclostationarity of transmit signals. Based on the cyclosta-tionary statistics of signals, a blind SNR estimator in AWGN channel was proposed. This estimator had no restrict on modulation mode and no need for transmitter to transmit known data. Simulat...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2006-01-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/74661721/ |
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| _version_ | 1841537414357581824 |
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| author | HUA Meng ZHU Jin-kang GONG Ming |
| author_facet | HUA Meng ZHU Jin-kang GONG Ming |
| author_sort | HUA Meng |
| collection | DOAJ |
| description | Upsampling and shaping filtering introduce the cyclostationarity of transmit signals. Based on the cyclosta-tionary statistics of signals, a blind SNR estimator in AWGN channel was proposed. This estimator had no restrict on modulation mode and no need for transmitter to transmit known data. Simulation results show this estimator yields better performance than other classic blind SNR estimators, such as M2M4 and SVR estimators in a large SNR domain. Also, in order to show the absolute levels of performance, the simulated performance was compared to a Cramer-Rao lower bound. |
| format | Article |
| id | doaj-art-ded2e9291c854da9b594c48c59c9c30b |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2006-01-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-ded2e9291c854da9b594c48c59c9c30b2025-01-14T08:37:47ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2006-01-0161374661721Blind SNR estimation based on cyclostationarityHUA MengZHU Jin-kangGONG MingUpsampling and shaping filtering introduce the cyclostationarity of transmit signals. Based on the cyclosta-tionary statistics of signals, a blind SNR estimator in AWGN channel was proposed. This estimator had no restrict on modulation mode and no need for transmitter to transmit known data. Simulation results show this estimator yields better performance than other classic blind SNR estimators, such as M2M4 and SVR estimators in a large SNR domain. Also, in order to show the absolute levels of performance, the simulated performance was compared to a Cramer-Rao lower bound.http://www.joconline.com.cn/zh/article/74661721/SNR estimationcyclostationarityCramer-Rao lower bound |
| spellingShingle | HUA Meng ZHU Jin-kang GONG Ming Blind SNR estimation based on cyclostationarity Tongxin xuebao SNR estimation cyclostationarity Cramer-Rao lower bound |
| title | Blind SNR estimation based on cyclostationarity |
| title_full | Blind SNR estimation based on cyclostationarity |
| title_fullStr | Blind SNR estimation based on cyclostationarity |
| title_full_unstemmed | Blind SNR estimation based on cyclostationarity |
| title_short | Blind SNR estimation based on cyclostationarity |
| title_sort | blind snr estimation based on cyclostationarity |
| topic | SNR estimation cyclostationarity Cramer-Rao lower bound |
| url | http://www.joconline.com.cn/zh/article/74661721/ |
| work_keys_str_mv | AT huameng blindsnrestimationbasedoncyclostationarity AT zhujinkang blindsnrestimationbasedoncyclostationarity AT gongming blindsnrestimationbasedoncyclostationarity |