非协作通信中的信噪比估计算法

Signal and Noise Ratio Estimation Method in Non-Cooperative Communication

  • 摘要: 研究基于信号协方差矩阵分解的信噪比估计算法. 该算法使用最小描述长度准则实现了信号空间维数的估计,进而实现信噪比估计. 在此基础上,提出了基于信号功率谱的信噪比估计算法. 由该方法计算出接收信号的功率谱,估计出有用信号的带宽,在有用信号频带外的噪声频带上估计出噪声的功率,从而估计出信噪比值. 仿真实验表明,当信噪比小于3dB时,基于信号功率谱的信噪比估计算法优于基于信号协方差矩阵分解算法.

     

    Abstract: Gives a blind signal and noise ratio(SNR) estimation method based on singular value decomposition of signal self-correlation matrix, and realizes the estimation of dimension of signal subspace by the principle of minimum descriptive length. Based on subspace decomposition ind, a method of SNR blind estimation based on power spectrum is proposed. We use power spectrum that is out of signal band to estimate the whole noise power. Then SNR value can be calculated out. This method does not need any prior information, and is suitable for all kind of non-constant envelope signals. The simulation results showed that when the SNR is lower than 3dB the method based on power spectrum works better than the method based on singular value decomposition.

     

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