文献类型：期刊文献

英文题名：LMPIT-Based Spectrum Sensing for Non-Circular Signals in Multi-Antenna Cognitive Radios

作者：Lai, Huadong[1];Luo, Peng[1];Liu, Mingxin[1];Xu, Jinqiang[1]

机构：[1]Guangdong Ocean Univ, Sch Elect & Informat Engn, Zhanjiang 524088, Peoples R China

年份：2025

卷号：24

期号：7

起止页码：5961

外文期刊名：IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS

收录：SCI-EXPANDED(收录号：WOS:001527222500019)、、EI(收录号：20251218090927)、Scopus(收录号：2-s2.0-105000503087)、WOS

基金：This work was supported in part by the Program for Scientific Research Start-Up Funds of Guangdong Ocean University under Grant 060302112316 and in part by the National Natural Science Foundation of China under Grant 62171143.

语种：英文

外文关键词：Sensors; Detectors; Covariance matrices; Standards; Vectors; Probability; Wireless sensor networks; Signal to noise ratio; Antennas; Training; Spectrum sensing; non-circular (NC) signals; locally most power invariant test (LMPIT); generalized Beta-based approximation; moment-matching

外文摘要：This paper addresses a robust spectrum sensing scheme for non-circular (NC) primary signals within the framework of locally most power invariant test (LMPIT). The proposed method is referred as the NCJT detector because it is deemed to be the NC generalization of the circular signals based John test. The proposed method utilizes the full second-order statistical properties of the NC signals by taking into consideration both standard covariance and complementary covariance, thereby exhibiting superiority in detection capability and robustness. Unlike the eigenvalue decomposition inherent in the eigenvalue-based detectors, the NCJT statistic is expressed as the ratio between the Frobenius norm and the trace of augmented covariance matrix, which delivers computational efficiency. The properties of invariance and constant false-alarm rate (CFAR) of the proposed method are theoretically confirmed. In addition, the distributions of the test statistic under both hypotheses are established with the support of generalized Beta-based approximation after deriving the first two moments of NCJT statistic with or without primary signals, facilitating us to approximate the probabilities of false alarm and detection. Numerical results are provided to examine the precision of our theoretical results and compare the sensing performance of our method with other detectors in various sensing scenarios.