CYCLOSTATIONARITY-BASED OFDM SIGNAL SENSING OVER DOUBLY-SELECTIVE FADING CHANNELS

In this paper,using cyclostationarity-based sensing method to detect the presence of Orthogonal Frequency Division Multiplexing(OFDM) signal over doubly-selective fading channels is studied.By approximating the channel with Basis Expansion Model(BEM),we derive the second-order cyclostationary statistics of the received OFDM signal over doubly-selective fading channels.Theoretical analysis indicates that new cyclostationary signatures produced by Doppler spread and multipath delay can be further exploited in the detecting process.Simulation examples demonstrate that the sensing methods using channel-induced cyclostationary features provide substantial improvements on detection performance.

Fault Early Diagnosis of Rolling Element Bearings Combining Wavelet Filtering and Degree of Cyclostationarity Analysis

The vibration signals of rolling element bearing are produced by a combination of periodic and random processes due to the machine’s rotation cycle and interaction with the real world. The combination of such components can give rise to signals, which have periodically time-varying ensemble statistical and are best considered as cyclostationary. When the early fault occurs, the background noise is very heavy, it is difficult to disclose the latent periodic components successfully using cyclostationary analysis alone. In this paper the degree of cyclostationarity is combined with wavelet filtering for detection of rolling element bearing early faults. Using the proposed entropy minimization rule. The parameters of the wavelet filter are optimized. This method is shown to be effective in detecting rolling element bearing early fault when cyclostationary analysis by itself fails.

Cyclic beamforming using fractional Fourier transform domain cyclostationarity

A minimum mean-squared error （MSE） beamforming algorithm employing the optimum fractional Fourier transform （Opt-FrFT） domain second-order cyclostationarity is proposed. This method can efficiently filter out the compact desired chirp signal, with a consequence that the cyclically uncorrelated interferences and stationary （colored） Gaussian noise are greatly suppressed in the Opt- FrFT domain. This improves the MSE minimization cyclic beamformer by reducing effectively the Opt-FrFY domain signal-noise cross terms in the presence of finite data length de-correlation operation. Simulation results show that the new method works well under a wide range of signal-to-noise ratio （SNR） and signal-to-interference ratio （SIR）.

Cyclic Beam Direction of Arrival Estimation Method for Ship Propeller Noise

In underwater acoustic applications,the conventional cyclic direction of arrival algorithm faces challenges,including a low signal-to-noise ratio and high bandwidth when compared with modulated frequencies.In response to these issues,this paper introduces a novel,robust,and broadband cyclic beamforming algorithm.The proposed method substitutes the conventional cyclic covariance matrix with the variance of the cyclic covariance matrix as its primary feature.Assuming that the same frequency band shares a common steering vector,the new algorithm achieves superior detection performance for targets with specific modulation frequencies while suppressing interference signals and background noise.Experimental results demonstrate a significant enhancement in the directibity index by 81%and 181%when compared with the traditional Capon beamforming algorithm and the traditional extended wideband spectral cyclic MUSIC(EWSCM)algorithm,respectively.Moreover,the proposed algorithm substantially reduces computational complexity to 1/40th of that of the EWSCM algorithm,employing frequency band statistical averaging and covariance matrix variance.

Blind MIMO Channel Estimation Based on Modulation-Induced Two-Cycle Cyclostationarity

In this paper, a novel approach is presented to the multiuser channelidentification . The approach makes use of the modulation-induced Cyclostationarity, capable ofidentifying individual channels of different users. By means of the decomposition of the cyclicspectrum method, the blind estimation of the channel can be achieved . The approach is rathersimple, with considerable advantages over existing techniques, and suitable for the multiuser uplink. The identifiabilily condition and its proof are also concluded in the paper. And finally the.simulation of identification algorithm is given.

A Specially Designed Modulation-Induced Cyclostationarity Scheme for Blind SISO Channel Identification and Equalization

A special Modulation-Induced Cyclostationarity(MIC)scheme is designed for the identification and equaliza-tion of FIR Single-Input-Single-Output(SISO)channel,with the property that the transmit power is constant and the re-ceiver needs only one antenna.The cyclic Wiener equalizer is presented based on the estimated channel.

Blind Multiuser Channel Identification Based on Rate Doubling and Modulation-Induced Cyclostationarity

In this paper, a novel approach is put forward to the multiuser channelidentification. The approach makes use of the modulation-induced Cyclostationarity to separate thesecond order cyclic statistics for every user, with the special features of one subspace for oneuser, so as to be able to identify individual channels of different users. In order to form aSingle-Input-Two-Output (SITO) system, the transmission rate is doubled by repeating at thetransmitters. The approach is rather simple, suitable for the multiuser uplink . And the channelidentifiability conditions with its proof are included in the paper, And finally the identificationalgorithm is proposed with simulation results.

Efficient channel blind estimator for multiuser system with conjugate cyclostationarity

The problem of blind channel identification in a multiuser system is considered in this article. For this purpose, a blind identification algorithm is proposed based on the conjugate cyclostationarity of the received signal. The new approach contains a two-stage identification procedure. First, the separation technique in the cyclic domain is used to separate the second-order cyclic statistics for each user. Second, a subspace algorithm based on the rational subspace theory is exploited to estimate the desired channel. Theoretical analysis and simulation results show that this algorithm is suitable for a multiuser system. Compared with other methods, the algorithm shows good performance even in a bad situation when the number of users is large and the diversity condition is unavailable.

Direction Finding with Cyclostationarity Analysis Against Frequency Interference

In this paper, a novel anti-interference direction finding(DF)method for amplitude comparison method based on cyclostationarity is proposed. With the periodic properties of the communication signals, the desired signal’s amplitude value can be effectively obtained even though there is an interference signal whose frequency spectrum overlaps with the desired signal in the environment,and the corresponding incident angle can be estimated accurately with the amplitude comparison method. The influence of interference signal on the amplitude comparison method is discussed and the proposed method’s theoretical feasibility is also analyzed. Compared with the conventional method,simulations are provided to demonstrate the anti-interference capability of the proposed method. The amplitude comparison DF system working at 2.44 GHz and 5.8 GHz is also constructed to verify its feasibility.

WAVELET BASED SPECTRAL CORRELATION METHOD FOR DPSK CHIP RATE ESTIMATION

A wavelet-based spectral correlation algorithm to detect and estimate BPSK signal chip rate is proposed. Simulation results show that the proposed method can correctly estimate the BPSK signal chip rate, which may be corrupted by the quadratic characteristics of the spectral correlation function, in a low SNR environment.

Neural Blind Beamformer for Cyclostationary Signals

A blind beamforming algorithm based on a neural network is presented according to the characteristic of cyclostationary signals. This method transforms the question of estimating beamformer weight vectors into the one of computing the SVD of the cross correlation matrix of array input signals and their frequency shift signals. A cross correlation neural network is introduced to compute the SVD of the cross correlation matrix so as to reduce the computational complexity and carry out the blind beanfforming more efficiently. The improved cross-coupled Hebbian learning rule presented can make the weights of the neural network converge much fast. Therefore, it is more promising in the practical use. This method can restrain noise and interference, simulation proves its correctness.

Asymptotic Analysis of Estimated Cyclic Cross-Correlation Function Between Stationary and Cyclostationary Processes

The cyclic cross-correlation between a stationary process and a cyclostationary process at cycle frequency α(≠ 0)is identically zero under an ideal condition, which indicates that a cyclic cross-correlation method performs much better than the conventional cross-correlation method in suppressing the stationary noise or interference. But unfortunately, the cyclic cross-correlation will not really approach zero due to the limited data length in some real conditions. In this paper, the quantitative relation between the data length and the estimated cyclic cross-correlation is deduced, and some useful conclusions are drawn, which are proven by some computer simulations. The conclusion in this paper is really useful for the practical application of cyclostationary signal processing.

SOME BLIND FRESH EQUALIZATION ALGORITHMS WITH ANTI-INTERFERENCE CAPABILITIES

Some novel blind FREquency-SHift (FRESH) equalizer algorithms are proposed for the equalization of Finite Impulse Response (FIR) single channel with anti-interference capabilities. These algorithms based on FRESH filter can work well without any training sequence. Simulation results show that the equalizer algorithms can effectively reject many types of interferences and the performances of these new equalizer algorithms are superior to the conventional equalizer algorithms.

Detection efficiency of cooperative spectrum sensing in cognitive radio network

Sensing the spectrum in a reliable and efficient manner is crucial to cognitive radio. To combat the channel fading suffered by the single radio, cooperative spectrum sensing is employed, to associate the detection of multiple radios. In this article, the optimization problem of detection efficiency under the constraint of detection probability is investigated, and an algorithm to evaluate the required radio number and sensing time for maximal detection efficiency is presented. To show the effect of cooperation on the detection efficiency, the proposed algorithm is applied to cooperative sensing using the spectral correlation detector under the Rayleigh flat fading channel.

Performance study of a class of cyclic weighted subspace fitting methods

Based on the idea of weighted subspace fitting and the asymptotic statistic characteristics of cyclic correlation matrices, the performance study of a class of cyclic weighted subspace fitting methods for direction estimation of cyclostationary signals is performed, and the analytic expressions of asymptotic variances of these methods are also given.

A design of multi-cycle detector for cognitive radios

Cognitive radio(CR)is a promising technology.The most fundamental problem of CR is spectrum sensing.Energy detector is often considered for spectrum sensing in CR,and if the noise power is exactly known,energy detector has admirable performance.However,in practice,noise power is always inexactly known.To solve this problem,Dandawate[Dandawate et al.IEEE Transactions on Signal Processing,1994,42(9):2355-2369]has proposed a nonparametric single-cycle detector based on cyclostationarity,which is robust to noise uncertainty.In this paper,based on Dandawate’s single-cycle detector,a joint multi-cycle detector is further proposed,which is also nonparametric and immune from noise uncertainty.Simulation results have shown the validity and superiority over single-cycle detector of the proposed detector.

A New Algorithm of Energy Suppression for Satellite Navigation

The satellite navigation anti-interference technique, especially space anti-interference technique, is subjected to many restrictions, such as cost, energy depletion, and so on, and the satellite signal strength is limited by the International Radio Advisory Committee, the International Telecommunication Union (ITU) and satellite companies. This paper focuses on satellite navigation systems, especially satellite navigation systems adopting direct sequence spread spectrum (DSSS). The notch filter is used to remove some frequencies from the pseudorandom code frequency spectrum making use of its cyclostationarity first, then the filtered pseudorandom code is modulated by the carrier to attain energy suppression, but the pseudorandom code autocorrelation characteristic stays unchanged. The feasibility of this algorithm is verified by simulation results.