A blind signal‐to‐jamming‐plus‐noise ratio estimation based on second‐order cyclostationarity under typical tone‐jamming and its CRLB. (14th April 2016)

• Record Type: Journal Article
• Authors: Yao, Fuqiang; Gao, Zezhong; Niu, Yingtao; Li, Yonggui
• Other Names: Ning Huansheng guestEditor.; El Baz Didier guestEditor.; Yang Laurence T. guestEditor.; Wang Rui guestEditor.
• Is Part Of: International journal of communication systems. Volume 30:Number 5(2017)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2016-04-14
• Subjects: CRLB -- cyclostationarity -- jamming -- signal‐to‐jamming‐plus‐noise ratio; Telecommunication systems -- Periodicals; 621.382
• DOI: 10.1002/dac.3133
• Languages: English
• ISSNs: 1074-5351

Abstract

Summary: In this paper, a blind signal‐to‐jamming‐plus‐noise ratio (SJNR) estimation under typical tone‐jamming is proposed in a Rayleigh fading channel. Based on the differences among communication signal, jamming, and noise in cyclostationarity, the proposed algorithm obtained SJNR values by using different parts of the cyclic autocorrelation matrix of received signals and applying the minimum square error (MSE) method to estimate the communication signal power and jamming‐plus‐noise power, respectively. Through deriving the Cramer–Rao lower bound (CRLB) for the SJNR estimation, the normalized MSE performance is examined. Simulation results show that the proposed estimation performs better than the subspace‐based eigenvalue decomposition estimation on a normalized estimation bias, and its normalized MSE performance is also closer to CRLB. Copyright © 2016 John Wiley & Sons, Ltd. Abstract : A blind signal‐to‐jamming‐plus‐noise ratio (SJNR) estimation under typical tone‐jamming is proposed in a Rayleigh fading channel. Based on the differences among communication signal, jamming, and noise in cyclostationarity, the proposed algorithm obtained SJNR values by using different parts of the cyclic‐autocorrelation matrix of received signals and applying the minimum ‐square ‐error (MSE) method to estimate the communication signal power and jamming‐plus‐noise power, respectively. Through deriving the Cramer‐Rao lower bound for the SJNR estimation, the normalized MSE performance is examined.