High-Sensitivity Acquisition of Ultrahigh Dynamic Direct Sequence Spread Spectrum Signals in Space Communications

According to the requirements of the high-sensitivity acquisition of Direct Sequence Spread Spectrum(DSSS) signals under ultrahigh dynamic environments in space communications, a three-dimensional joint search of the phase of Pseudo-Noise-code(PN-code),Doppler frequency and its rate-of-change is presented to achieve high sensitivity in sensing high-frequency dynamics. By eliminating the correlation peak loss caused by ultrahigh Doppler frequency and its rate-of-change offset,the proposed method improves the acquisition sensitivity by increasing the non-coherent accumulation time. The validity of the algorithm is proved by theoretical analysis and simulation results. It is shown that signals with a carrier- to-noise ratio as low as 39 dBHz can be captured with high performance when the Doppler frequency is up to ±1 MHz and its rate-of-change is up to ±200 kHz/s.

New Acquisition Algorithm for Direct Sequence Spread Spectrum Signals

Aiming at improving acquisition performance for direct sequence spread spectrum （DSSS） signals, a new acquisition algorithm based on fast Fourier transform （FFT） is proposed. The code phases are parallel searched throughout the Doppler frequency domain. Since the influence of Doppler frequency errors on peak-to- average ratios of correlation power shows a pattern similar to the sinc function, it is our belief that by judging on peak-to-average ratios for different Doppler frequency errors false alarm probabilities should be lowered. Analyses have supported the underlying principle of this new algorithm. Simulation results have also indicated that the new algorithm can effectively improve the acquisition performance for DSSS signals.

Research on Estimator and Testing Acquisition Schemes in Direct Sequence Spectrum Spreading Systems

Serveral methods for the pararrel acquisition of a PN sequence in a baseband direct sequence spread spectrum system are investigated. Four different kinds of schemes are considered: the optimal estimation scheme, the locally optimal estimation scheme, the optimal testing searches and the locally optimal testing scheme. In the four kinds of parallel acquisition schemes, the expressions for the probability of error are given and compared with the actual error probabilities obtained via Monte Carlo simulation. We also outline a technique that can be suboptimal because of a large amount of hardware and computation when using the parallel acquisition schemes.

Several Modulation in Direct-Sequence Spectrum-Spread Systems

Performances of BPSK, balanced quaternary modulation, dual quaternary modulation and complex quaternary modulation in direct sequence spectrum spread (DS SS) system are discussed in this paper. Based on the criterion the power of original signal is the same, it is shown that complex quaternary modulation has the best performance, and dual quaternary modulation degrades 2dB. Moreover, the frequency efficient of the two modulations is 2bit/Hz. Balanced quaternary has the same performance as BPSK with frequency efficient 1bit/Hz.

Non-Supervised Learning for Spread Spectrum Signal Pseudo-Noise Sequence Acquisition

An idea of estimating the direct sequence spread spectrum（DSSS） signal pseudo-noise（PN） sequence is presented. Without the apriority knowledge about the DSSS signal in the non-cooperation condition, we propose a self-organizing feature map（SOFM） neural network algorithm to detect and identify the PN sequence. A non-supervised learning algorithm is proposed according the Kohonen rule in SOFM. The blind algorithm can also estimate the PN sequence in a low signal-to-noise（SNR） and computer simulation demonstrates that the algorithm is effective. Compared with the traditional correlation algorithm based on slip-correlation, the proposed algorithm＇s bit error rate（BER） and complexity are lower.

Fast method for spreading sequence estimation of DSSS signal based on maximum likelihood function

To estimate the spreading sequence of the direct sequence spread spectrum (DSSS) signal, a fast algorithm based on maximum likelihood function is proposed, and the theoretical derivation of the algorithm is provided. By simplifying the objective function of maximum likelihood estimation, the algorithm can realize sequence synchronization and sequence estimation via adaptive iteration and sliding window. Since it avoids the correlation matrix computation, the algorithm significantly reduces the storage requirement and the computation complexity. Simulations show that it is a fast convergent algorithm, and can perform well in low signal to noise ratio (SNR).

Low complexity method for spreading sequence estimation of DSSS signal in non-cooperative communication systems

It is a necessary step to estimate the spreading sequence of direct sequence spread spectrum （DSSS） signal for blind despreading and demodulation in non-cooperative communications. Two innovative and effective detection statistics are proposed to implement the synchronization and spreading sequence estimation procedure. The proposed algorithm also has a low computational complexity with only linear additions and modifications. Theoretical analysis and simulation results show that the algorithm performs quite well in low SNR environment, and is much better than all the existing typical algorithms with a comprehensive consideration both in performance and computational complexity.

Neural network approach to blindestimation of PN spreading sequence in lower SNR DS/SS signals

An approach based on discrete Karhunen-Loeve transformation of the DS/SS signals is proposed to estimate PN sequence in lower S/N ratio DS/SS signals. Characteristics of self-organization and principle components extraction of unsupervised neural networks are exploited adequately. Theoretical analysis and experimental results are provided to show that this approach can work well on the lower S/N ratio input signals.

A Neural Network Approach to Blind Estimation of PN Spreading Sequence in DS/SS Signals

In this paper, a new approach is proposed to estimate pseudo noise(PN) sequence in the lower SNR DS/SS signals blindly. This method utilizes the characteristics of self-organization, principal components analysis and extraction of unsupervised neural networks adequately, in addition to its higher-speed operation ability, successfully solve the difficult problem about PN sequence blind estimation. The theoretic analysis and experimental results show that this approach can work very well on lower SNR input signals.

Approach to blind estimation of the PN sequence in DS-SS signals with residual carrier

This paper presents an approach of singular value de- composition plus digital phase lock loop to solve the difficult problem of blind pseudo-noise （PN） sequence estimation in low signal to noise ratios （SNR） direct sequence spread spectrum （DS-SS） signals with residual carrier. This approach needs some given parameters, such as the period and code rate of PN sequence. The received signal is firstly sampled and divided into non-overlapping signal vectors according to a temporal window, whose duration is two periods of PN sequence. An autocorrelation matrix is then computed and accumulated by those signal vectors one by one. The PN sequence with residual carrier can be estimated by the principal eigenvector of the autocorrelation matrix. Further more, a digital phase lock loop is used to process the estimated PN sequence, it estimates and tracks the residual carrier and removes the residual carrier in the end. Theory analysis and computer simulation results show that this approach can effectively realize the PN sequence blind estimation from the input DS-SS signals with residual carrier in lower SNR.

An underwater acoustic direct sequence spread spectrum communication system using dual spread spectrum code

With the goal of achieving high stability and reliability to support underwater point-to-point communications and code division multiple access(CDMA) based underwater networks, a direct sequence spread spectrum based underwater acoustic communication system using dual spread spectrum code is proposed. To solve the contradictions between the information data rate and the accuracy of Doppler estimation, channel estimation, and frame synchronization, a data frame structure based on dual spread spectrum code is designed. A long spread spectrum code is used as the training sequence, which can be used for data frame detection and synchronization, Doppler estimation, and channel estimation. A short spread spectrum code is used to modulate the effective information data. A delay cross-correlation algorithm is used for Doppler estimation, and a correlation algorithm is used for channel estimation. For underwater networking, each user is assigned a different pair of spread spectrum codes. Simulation results show that the system has a good anti-multipath, anti-interference, and anti-Doppler performance, the bit error rate can be smaller than 10^(-6) when the signal-to-noise ratio is larger than-10 dB, the data rate can be as high as 355 bits/s, and the system can be used in the downlink of CDMA based networks.

Code-aided Interference Suppression in Direct Sequence Spread Spectrum Systems with Eigenvector Sign Spreading Code

For direct sequence spread spectrum (DSSS) communication systems suffering interference, it is known that code-aided interference suppression technique outperforms all of the previous linear or nonlinear methods. In this paper, we proposed an improved code-aided technique which can improve the system performance greatly by using the eigenvector sign (EVS) spreading sequence which depends on the statistical characteristics of the interference and the thermal noise.

Reconfigurable Intelligent Surface-Based Hybrid Phase and Code Modulation for Symbiotic Radio

Reconfigurable intelligent surface(RIS)-assisted symbiotic radio is a spectrum-and energy-efficient communication paradigm,in which an RIS performs passive beamforming to enhance active transmission,while using the electromagnetic waves from the active transmission for additional information transfer(i.e.,passive transmission).In this paper,a hybrid RIS-based modulation,termed hybrid phase and code modulation(HPCM),is proposed to improve the reliability of RIS-assisted symbiotic radio.In RIS-HPCM,the RIS simultaneously performs direct sequence spread spectrum and passive beamforming on incident signals.Moreover,both the spreading code and phase offset are exploited to carry the RIS’s own information.A low-complexity detector is designed,in which the receiver first detects the spreading codes and then demodulates the constellation symbols.We analyze the bit error rate(BER)performance of RIS-HPCM over Rician fading channels.BER upper bounds and approximate BER expressions are derived in closed-form for maximum-likelihood and low-complexity detectors,respectively.Simulation results in terms of BER verify the analysis and show the superiority of RIS-HPCM over the existing RIS-based modulation.

Concatenated Trellis Coding and CPM for DS/SSMA Communications in Rayleigh Fading Channel

In this paper, direct sequence spread spectrum multiple access (DS/SSMA) communication system employing serially concatenated trellis coded modulation (TCM) and continuous phase modulation (CPM) over flat Rayleigh fading channel are presented. The performance of this concatenated TCM/CPM DS/SSMA system is exploited by the theoretical analysis and numerical simulations. The results demonstrate that significant improvements in error probability of this DS/SSMA system over the system with single TCM or CPM of different modulation indices can be achieved under the same conditions.

Novel LFM Jammer Suppression Algorithm for DSSS in FRFT Domain

A novel algorithm is proposed to resolve the defects in the traditional linear frequency modulation(LFM)jamming suppression algorithm in the fractional Fourier transform(FRFT)domain.The traditional LFM jamming suppression algorithm in the FRFT domain has some defects.For example,the exact threshold is difficult to set and both the signal-to-noise ratio(SNR)loss and spectrum leakage are serious in strong jamming-to-signal ratio(JSR)situations.Windowing,overlapping and inverse windowing techniques are used in the FRFT domain to reduce the spectrum leakage and the SNR loss.Under the condition that only the direct sequence spread spectrum(DSSS)signal and white Gaussian noise are present,the amplitude of the received signal after FRFT is assumed to be Rayleigh distributed.Based on the distribution characteristic,hypothesis testing is used to suppress the jamming spectrum using the algorithm.Simulation results show that the performance of proposed algorithm is better than that of the conventional algorithms,especially in a strong jamming and multi component LFM jamming environment.

Adaptive median threshold algorithm used in FDIS of DSSS receivers

For direct sequence spread spectrum （DSSS） receivers, the capability of rejecting narrow-band interference can be significantly improved by a process of frequency-domain interference suppression （FDIS）. The key issue of this process is how to determine a threshold to eliminate interference in the frequency domain, which has been extensively studied. However, these previous methods are tedious or very complex. A simple and ef- ficient algorithm based on medians is proposed. The elimination threshold is only related to the median by a scale factor, which can be obtained by the numerical analysis. Simulation results show that the algorithm provides excellent narrow-band interfer- ence suppression while only slightly degrading the signal-to-noise ratio （SNR）. A one-pass algorithm using logarithmic segmentation is further derived to estimate medians with low computational complexity. Finally, the FDIS is implemented in a field programmable gate array （FPGA） of Xilinx. Experiments are carried out by connecting the FDIS FPGA to a DSSS receiver, and the results show that the receiver has an effective countermeasure for a 60 dB interference-to-signal ratio （ISR）.

New acquisition decision algorithm for multiple access interference suppression in DSSS system

For decreasing the multiple access interference of weaker signal acquisition in direct sequence spread spectrum（DSSS） systems,a new single decision algorithm is presented.The maximum value of correlation results is conventionally detected.However,there may be not only one strong peak among correlation results when the cross-correlation noise is strong enough to affect the correlation results.The proposed algorithm decreases the false alarm probability through the decision of the ratio of the maximum value and the second maximum value of the correlation results.Theoretical analysis and simulation results indicate that the proposed algorithm effectively suppresses the acquisition problem of multiple access interference in DSSS system.

Rejection of Linear FM Interference in DSSS System Based on Fractional Fourier Transform

A new method for the rejection of linear frequency modulation (LFM) interference in direct sequence spread spectrum (DSSS) system based on the fractional Fourier transform is proposed, and the configuration of the receiver with an interference exciser is also presented. Based on the property that the fractional Fourier transform of a signal is equivalent to rotating the signal in the time-frequency plane, the received signal is transform into a certain fractional Fourier domain, this transform will result in the least spectrum overlap between the signal and interference. Then, a narrowband filter is exploited to extract most of the interference energy. The performance analyses show that remarkable improvements in signal-to-noise ratio (SNR) and bit-error-ratio (BER) are obtained.

Subspace decomposition-based correlation matrix multiplication

The correlation matrix, which is widely used in eigenvalue decomposition （EVD） or singular value decomposition （SVD）, usually can be denoted by R = E[yiy＇i]. A novel method for constructing the correlation matrix R is proposed. The proposed algorithm can improve the resolving power of the signal eigenvalues and overcomes the shortcomings of the traditional subspace methods, which cannot be applied to low SNR. Then the proposed method is applied to the direct sequence spread spectrum （DSSS） signal＇s signature sequence estimation. The performance of the proposed algorithm is analyzed, and some illustrative simulation results are presented.

AUDIO STEGANALYSIS OF DSSS BASED ON STATISTICAL MOMENTS OF HISTOGRAM

Compared with the histogram of Discrete Cosine Transform (DCT) coefficients before the Direct Sequence Spread Spectrum (DSSS) embedding, the peak value of the histogram after the embedding decreases and expands toward the border. Based on the property, an audio steganalysis of DSSS based on statistical moments of histogram is proposed. The statistical moments of the histogram in DCT domain and its frequency domain and the statistical moments of the histogram of the wavelet coefficients of every level in frequency domain are calculated as the features of classification. Support Vector Machine (SVM) is exploited as the classifier. Experimental results show that the proposed technique is effective on the DSSS embedding in DCT domain using different embedding length, and the average detection rate is 91.75%.