A subspace-based blind Signal-to-Noise Ratio (SNR) estimation algorithm for digital bandpass signals in Additive White Gaussian Noise (AWGN) channel is discussed. The lower bounds of the mean and variance of the estim...A subspace-based blind Signal-to-Noise Ratio (SNR) estimation algorithm for digital bandpass signals in Additive White Gaussian Noise (AWGN) channel is discussed. The lower bounds of the mean and variance of the estimation are derived, and simulations are performed for the commonly used digital bandpass signals, such as MPSK (M=2, 4, 8), MFSK (M=2, 4) and MQAM (M=16, 64, 128, 256) signals. Theoretical analyses and simulation results indicate that the proposed algorithm is ef- fective even when the SNR is below 0dB. Furthermore, the algorithm can provide a blind estimator in that it needs neither the parameters of the received signals, such as the carrier frequency, symbol rate and modulation scheme, nor the synchronization of the system.展开更多
A new quadrature sampling technique for arbitrary bandpass signal within baseband sampling rate is presented. The input bandpass signal whose carrier frequency lies in the A/D baseband sampling rate is first decimated...A new quadrature sampling technique for arbitrary bandpass signal within baseband sampling rate is presented. The input bandpass signal whose carrier frequency lies in the A/D baseband sampling rate is first decimated by factor 2 and modulated by (- 1)n, and then is interpolated by a linear phase FIR all-pass filter, finally the modulated complex envelope of bandpass signal can be produced.展开更多
In this paper, a new signal separation method mainly for AM-FM components blended in noises is revisited based on the new derived time-varying bandpass filter (TVBF), which can separate the AM-FM components whose freq...In this paper, a new signal separation method mainly for AM-FM components blended in noises is revisited based on the new derived time-varying bandpass filter (TVBF), which can separate the AM-FM components whose frequencies have overlapped regions in Fourier transform domain and even have crossed points in time-frequency distribution (TFD) so that the proposed TVBF seems like a “soft-cutter” that cuts the frequency domain to snaky slices with rational physical sense. First, the Hilbert transform based decomposition is analyzed for the analysis of nonstationary signals. Based on the above analysis, a hypothesis under a certain condition that AM-FM components can be separated successfully based on Hilbert transform and the assisted signal is developed, which is supported by representative experiments and theoretical performance analyses on a error bound that is shown to be proportional to the product of frequency width and noise variance. The assisted signals are derived from the refined time-frequency distributions via image fusion and least squares optimization. Experiments on man-made and real-life data verify the efficiency of the proposed method and demonstrate the advantages over the other main methods.展开更多
提出一种R ay le igh衰落信道条件下的多载波调制盲识别算法,用以区分多载波调制信号(如OFDM)和数字单载波调制信号(如M PSK,M QAM,M FSK)。该算法不需要预先知道信号的载波频率和波特率,只需从中频信号直接进行识别处理。算法中利用信...提出一种R ay le igh衰落信道条件下的多载波调制盲识别算法,用以区分多载波调制信号(如OFDM)和数字单载波调制信号(如M PSK,M QAM,M FSK)。该算法不需要预先知道信号的载波频率和波特率,只需从中频信号直接进行识别处理。算法中利用信号的高阶统计量作为分类特征,采用信噪比(SNR)与特征参数联合估计的方法完成自动分类,仿真结果表明在SNR高于0 dB时识别率大于95%。展开更多
文摘A subspace-based blind Signal-to-Noise Ratio (SNR) estimation algorithm for digital bandpass signals in Additive White Gaussian Noise (AWGN) channel is discussed. The lower bounds of the mean and variance of the estimation are derived, and simulations are performed for the commonly used digital bandpass signals, such as MPSK (M=2, 4, 8), MFSK (M=2, 4) and MQAM (M=16, 64, 128, 256) signals. Theoretical analyses and simulation results indicate that the proposed algorithm is ef- fective even when the SNR is below 0dB. Furthermore, the algorithm can provide a blind estimator in that it needs neither the parameters of the received signals, such as the carrier frequency, symbol rate and modulation scheme, nor the synchronization of the system.
文摘A new quadrature sampling technique for arbitrary bandpass signal within baseband sampling rate is presented. The input bandpass signal whose carrier frequency lies in the A/D baseband sampling rate is first decimated by factor 2 and modulated by (- 1)n, and then is interpolated by a linear phase FIR all-pass filter, finally the modulated complex envelope of bandpass signal can be produced.
文摘In this paper, a new signal separation method mainly for AM-FM components blended in noises is revisited based on the new derived time-varying bandpass filter (TVBF), which can separate the AM-FM components whose frequencies have overlapped regions in Fourier transform domain and even have crossed points in time-frequency distribution (TFD) so that the proposed TVBF seems like a “soft-cutter” that cuts the frequency domain to snaky slices with rational physical sense. First, the Hilbert transform based decomposition is analyzed for the analysis of nonstationary signals. Based on the above analysis, a hypothesis under a certain condition that AM-FM components can be separated successfully based on Hilbert transform and the assisted signal is developed, which is supported by representative experiments and theoretical performance analyses on a error bound that is shown to be proportional to the product of frequency width and noise variance. The assisted signals are derived from the refined time-frequency distributions via image fusion and least squares optimization. Experiments on man-made and real-life data verify the efficiency of the proposed method and demonstrate the advantages over the other main methods.
文摘提出一种R ay le igh衰落信道条件下的多载波调制盲识别算法,用以区分多载波调制信号(如OFDM)和数字单载波调制信号(如M PSK,M QAM,M FSK)。该算法不需要预先知道信号的载波频率和波特率,只需从中频信号直接进行识别处理。算法中利用信号的高阶统计量作为分类特征,采用信噪比(SNR)与特征参数联合估计的方法完成自动分类,仿真结果表明在SNR高于0 dB时识别率大于95%。
