文献类型：期刊文献

英文题名：Balancing Detection Efficacy and Robustness: A Weighted Sign-Energy Detector for Spectrum Sensing

作者：Mou, Jie[1];Huang, Guanna[1];Lai, Huadong[2];Dai, Jisheng[3];Xu, Weichao[1]

机构：[1]Guangdong Univ Technol, Sch Automat, Guangzhou 510006, Peoples R China;[2]Guangdong Ocean Univ, Sch Elect & Informat Engn, Zhanjiang 524088, Peoples R China;[3]Donghua Univ, Coll Informat Sci & Technol, Shanghai 201620, Peoples R China

年份：2026

卷号：15

起止页码：5427

外文期刊名：IEEE WIRELESS COMMUNICATIONS LETTERS

收录：SCI-EXPANDED(收录号：WOS:001885935400007)、、EI(收录号：20263921559701)、Scopus(收录号：2-s2.0-105051659574)、WOS

基金：This work was supported in part by the National Natural Science Foundation of China under Grant 62571146 and Grant 62501175; in part by Guangdong Science and Technology Department under Grant 2024A1515011803, Grant 2026A1515011625, and Grant 2026A1515011437; and in part by the Natural Science Foundation of Shanghai Basic Research Funding under Grant 25ZR1401002. The associate editor coordinating the review of this article and approving it for publication was M.-K. Chang.

语种：英文

外文关键词：Noise; Detectors; Signal to noise ratio; Energy; Signal detection; Modeling; Gaussian noise; Antennas; Correlation; Instant messaging; Spectrum sensing; robust detection; non-Gaussian noise; Bernoulli-Gaussian mixture; deflection coefficient

外文摘要：In spectrum sensing, conventional detectors suffer severe performance degradation under impulsive noise, whereas existing robust detectors often compromise detection efficacy in pure Gaussian environments. To address this trade-off, this letter proposes a Weighted Sign-Energy Detector (WSED). By decomposing the structure of the exact likelihood ratio test (LRT), the WSED combines an energy component with a robust sign correlator (SC). We derive the exact and asymptotic statistical moments of the proposed statistic and optimize the combination weights by maximizing the deflection coefficient (DC). Furthermore, a practical sample-based weight implementation strategy is developed. Numerical results demonstrate that the WSED maintains robustness against impulsive outliers while remaining effective in pure Gaussian environments.