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A blind signal‐to‐jamming‐plus‐noise ratio estimation based on second‐order cyclostationarity under typical tone‐jamming and its CRLB
Author(s) -
Yao Fuqiang,
Gao Zezhong,
Niu Yingtao,
Li Yonggui
Publication year - 2016
Publication title -
international journal of communication systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.344
H-Index - 49
eISSN - 1099-1131
pISSN - 1074-5351
DOI - 10.1002/dac.3133
Subject(s) - jamming , cramér–rao bound , upper and lower bounds , noise (video) , computer science , algorithm , statistics , signal to noise ratio (imaging) , rayleigh fading , mean squared error , noise power , autocorrelation , mathematics , speech recognition , estimation theory , telecommunications , channel (broadcasting) , fading , power (physics) , artificial intelligence , physics , mathematical analysis , quantum mechanics , image (mathematics) , thermodynamics
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.