吴皓,张涛,陈跃,等. 基于相互无偏基和拟合优度检验的频谱感知方法[J]. 电波科学学报,2022,37(1):67-72. DOI: 10.12265/j.cjors.2021008
      引用本文: 吴皓,张涛,陈跃,等. 基于相互无偏基和拟合优度检验的频谱感知方法[J]. 电波科学学报,2022,37(1):67-72. DOI: 10.12265/j.cjors.2021008
      WU H, ZHANG T, CHEN Y, et al. Spectrum sensing based on MUB and goodness of fit test[J]. Chinese journal of radio science,2022,37(1):67-72. (in Chinese). DOI: 10.12265/j.cjors.2021008
      Citation: WU H, ZHANG T, CHEN Y, et al. Spectrum sensing based on MUB and goodness of fit test[J]. Chinese journal of radio science,2022,37(1):67-72. (in Chinese). DOI: 10.12265/j.cjors.2021008

      基于相互无偏基和拟合优度检验的频谱感知方法

      Spectrum sensing based on MUB and goodness of fit test

      • 摘要: 频谱感知是认知无线电中最重要的技术之一. 基于相互无偏基(mutually unbiased bases, MUB)矩阵,提出了改进的KS(Kolmogorov-Smirnov)拟合优度检验方法. 所提方法充分利用MUB的弱相关性,对接收的样本信号做数据处理,以扩大样本的规模,从而提高检验性能. 蒙特卡洛模拟仿真结果表明,在接收样本数量有限并且噪声服从高斯分布的情况下,本文提出的方法对于接收信号的检测概率要高于常规的KS检验方法.

         

        Abstract: Spectrum sensing is one of the most important technologies in cognitive radio. Based on the mutational unbiased bases (MUB) matrices and goodness of fit test, a novel spectrum sensing method based on the traditional Kolmogorov-Smirnov (KS) test is proposed in this paper. Specifically, by using MUB matrices to process the received samples, new samples with low correlation are generated, and thus, the number of samples is enlarged, and its sensing performance is improved. Simulation results show that when the number of received samples is limited and the noise is subject to Gaussian distribution, detection probability of the proposed method is higher than the traditional KS test method.

         

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