Carrier frequency and symbol rate estimation are the main contents of parameter estimation,which is the basis of modulation recognition and further processing of signals especially in non-cooperative communication.Wit...Carrier frequency and symbol rate estimation are the main contents of parameter estimation,which is the basis of modulation recognition and further processing of signals especially in non-cooperative communication.With the development of wireless communication,the signal transmission environment has become increasingly bad,causing more difficulties in parameter estimation.It is well known that the signal cycle spectrum is robust to noises and signal parameters are closely related.In practice,it is impossible to calculate the cyclic spectrum of infinite length data signals.When using finite length data to obtain a cycle spectrum,the truncation noise is induced,resulting in interference.It is necessary to overcome the influence of noises in order to improve the detection ability of discrete spectral lines.An improved method of the discrete spectral line extraction algorithm is proposed by reflecting the amplitude advantage of discrete spectral lines through salient features of continuous noises in discrete spectral line neighborhood.展开更多
The traditional cyclical spectrum density（CSD） method is widely used to analyze the fault signals of rolling bearing. All modulation frequencies are demodulated in the cyclic frequency spectrum. Consequently, recogn...The traditional cyclical spectrum density（CSD） method is widely used to analyze the fault signals of rolling bearing. All modulation frequencies are demodulated in the cyclic frequency spectrum. Consequently, recognizing bearing fault type is difficult. Therefore, a new CSD method based on kurtosis（CSDK） is proposed. The kurtosis value of each cyclic frequency is used to measure the modulation capability of cyclic frequency. When the kurtosis value is large, the modulation capability is strong. Thus, the kurtosis value is regarded as the weight coefficient to accumulate all cyclic frequencies to extract fault features. Compared with the traditional method, CSDK can reduce the interference of harmonic frequency in fault frequency, which makes fault characteristics distinct from background noise. To validate the effectiveness of the method, experiments are performed on the simulation signal, the fault signal of the bearing outer race in the test bed, and the signal gathered from the bearing of the blast furnace belt cylinder. Experimental results show that the CSDK is better than the resonance demodulation method and the CSD in extracting fault features and recognizing degradation trends. The proposed method provides a new solution to fault diagnosis in bearings.展开更多
随着通信技术的发展,频谱感知技术已经成为解决频谱资源稀缺的重要解决手段之一。针对传统的频谱感知方法在低信噪比(Signal to Noise Ratio,SNR)下准确率较低的问题,提出一种基于残差神经网络和注意力机制相结合的正交频分复用(Orthogo...随着通信技术的发展,频谱感知技术已经成为解决频谱资源稀缺的重要解决手段之一。针对传统的频谱感知方法在低信噪比(Signal to Noise Ratio,SNR)下准确率较低的问题,提出一种基于残差神经网络和注意力机制相结合的正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)频谱感知方法。将频谱感知问题转化为图像二分类任务。通过分析OFDM信号的循环自相关特征,将其灰度处理以生成循环自相关灰度图像。利用改进后的残差神经网络进行训练,提取这些灰度图像的深层特征,使用测试数据验证所得到的频谱感知模型。仿真实验结果表明,在低SNR条件下,所提方法表现出更出色的频谱感知性能,优于传统频谱感知技术。展开更多
This paper addresses the problem of the opportunistic spectrum access in Cognitive Radio. Indeed, most spectrum sensing algorithms suffer from a high computational cost to achieve the detection process. They need a pr...This paper addresses the problem of the opportunistic spectrum access in Cognitive Radio. Indeed, most spectrum sensing algorithms suffer from a high computational cost to achieve the detection process. They need a prior knowledge of signal characteristics and present a bad performance in low Signal to Noise Ratio (SNR) environment. The choice of the optimal detection threshold is another issue for these spectrum sensing algorithms. To overcome the limits of spectrum detectors, we propose in this paper, a blind detection method based on the cyclostationary features of communication signals. Our detector evaluates the level of hidden periodicity contained in the observed signal to make decision on the state of a bandwidth. In order to reduce the computational cost, we take advantage of the FFT Accumulation Method to estimate the cyclic spectrum of the observed signal. Then, we generate the Cyclic Domain Profile of the cyclic spectrum which allows us to evaluate the level of the hidden periodicity in the signal. This level of periodicity is quantified through the crest factor of Cyclic Domain Profile, which represents the decision statistic of the proposed detector. We have established the analytic expression of the optimal threshold of the detection and the probability of detection to evaluate the performance of the proposed detector. Simulation results show that the proposed detector is able to detect the presence of a communication signal on a bandwidth in a very low SNR scenario.展开更多
M-ary spread spectrum technique has been found wide applications in wireless communications, but it needs too many orthogonal spreading codes and its despreading/demodulation is quite complex computationally, which li...M-ary spread spectrum technique has been found wide applications in wireless communications, but it needs too many orthogonal spreading codes and its despreading/demodulation is quite complex computationally, which limit its wider applications. This paper proposes a novel scheme for Code Division Multiple Access (CDMA) communication systems based on M-ary spread spectrum, where only one prototype spreading code is assigned to each user and the codes for different users are orthogonal or quasi-orthogonal with each other. The M spreading codes of each user to represent K bits data are generated by circularly shifting the assigned code and reversing its polarity. The spreading codes generated like that are called as BiOrthogonal Cyclic Codes (BOCCs). At the receiver of the system, a transform domain matched-filter implemented by means of Fast Fourier Transform (FFT) is employed to despread and demodulate the received signals, which has very low computational complexity. The results of simulation experiments and bit-error performance analysis show that the proposed scheme is practical and very useful in many cases.展开更多
基金supported by the National Key R&D Program of China(2016YFB0800203)
文摘Carrier frequency and symbol rate estimation are the main contents of parameter estimation,which is the basis of modulation recognition and further processing of signals especially in non-cooperative communication.With the development of wireless communication,the signal transmission environment has become increasingly bad,causing more difficulties in parameter estimation.It is well known that the signal cycle spectrum is robust to noises and signal parameters are closely related.In practice,it is impossible to calculate the cyclic spectrum of infinite length data signals.When using finite length data to obtain a cycle spectrum,the truncation noise is induced,resulting in interference.It is necessary to overcome the influence of noises in order to improve the detection ability of discrete spectral lines.An improved method of the discrete spectral line extraction algorithm is proposed by reflecting the amplitude advantage of discrete spectral lines through salient features of continuous noises in discrete spectral line neighborhood.
基金Supported by Beijing Higher Education Young Elite Teacher Project(Grant No.YETP0373)National Natural Science Foundation of China(Grant Nos.51004013,50905013)
文摘The traditional cyclical spectrum density（CSD） method is widely used to analyze the fault signals of rolling bearing. All modulation frequencies are demodulated in the cyclic frequency spectrum. Consequently, recognizing bearing fault type is difficult. Therefore, a new CSD method based on kurtosis（CSDK） is proposed. The kurtosis value of each cyclic frequency is used to measure the modulation capability of cyclic frequency. When the kurtosis value is large, the modulation capability is strong. Thus, the kurtosis value is regarded as the weight coefficient to accumulate all cyclic frequencies to extract fault features. Compared with the traditional method, CSDK can reduce the interference of harmonic frequency in fault frequency, which makes fault characteristics distinct from background noise. To validate the effectiveness of the method, experiments are performed on the simulation signal, the fault signal of the bearing outer race in the test bed, and the signal gathered from the bearing of the blast furnace belt cylinder. Experimental results show that the CSDK is better than the resonance demodulation method and the CSD in extracting fault features and recognizing degradation trends. The proposed method provides a new solution to fault diagnosis in bearings.
文摘随着通信技术的发展,频谱感知技术已经成为解决频谱资源稀缺的重要解决手段之一。针对传统的频谱感知方法在低信噪比(Signal to Noise Ratio,SNR)下准确率较低的问题,提出一种基于残差神经网络和注意力机制相结合的正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)频谱感知方法。将频谱感知问题转化为图像二分类任务。通过分析OFDM信号的循环自相关特征,将其灰度处理以生成循环自相关灰度图像。利用改进后的残差神经网络进行训练,提取这些灰度图像的深层特征,使用测试数据验证所得到的频谱感知模型。仿真实验结果表明,在低SNR条件下,所提方法表现出更出色的频谱感知性能,优于传统频谱感知技术。
文摘This paper addresses the problem of the opportunistic spectrum access in Cognitive Radio. Indeed, most spectrum sensing algorithms suffer from a high computational cost to achieve the detection process. They need a prior knowledge of signal characteristics and present a bad performance in low Signal to Noise Ratio (SNR) environment. The choice of the optimal detection threshold is another issue for these spectrum sensing algorithms. To overcome the limits of spectrum detectors, we propose in this paper, a blind detection method based on the cyclostationary features of communication signals. Our detector evaluates the level of hidden periodicity contained in the observed signal to make decision on the state of a bandwidth. In order to reduce the computational cost, we take advantage of the FFT Accumulation Method to estimate the cyclic spectrum of the observed signal. Then, we generate the Cyclic Domain Profile of the cyclic spectrum which allows us to evaluate the level of the hidden periodicity in the signal. This level of periodicity is quantified through the crest factor of Cyclic Domain Profile, which represents the decision statistic of the proposed detector. We have established the analytic expression of the optimal threshold of the detection and the probability of detection to evaluate the performance of the proposed detector. Simulation results show that the proposed detector is able to detect the presence of a communication signal on a bandwidth in a very low SNR scenario.
基金Supported by the National Natural Science Foundation of China (No.60172029).
文摘M-ary spread spectrum technique has been found wide applications in wireless communications, but it needs too many orthogonal spreading codes and its despreading/demodulation is quite complex computationally, which limit its wider applications. This paper proposes a novel scheme for Code Division Multiple Access (CDMA) communication systems based on M-ary spread spectrum, where only one prototype spreading code is assigned to each user and the codes for different users are orthogonal or quasi-orthogonal with each other. The M spreading codes of each user to represent K bits data are generated by circularly shifting the assigned code and reversing its polarity. The spreading codes generated like that are called as BiOrthogonal Cyclic Codes (BOCCs). At the receiver of the system, a transform domain matched-filter implemented by means of Fast Fourier Transform (FFT) is employed to despread and demodulate the received signals, which has very low computational complexity. The results of simulation experiments and bit-error performance analysis show that the proposed scheme is practical and very useful in many cases.
