Efficient detection of truncated m-sequences using higher order statistics

This paper presents an analysis of delay-locked loops in direct spreading code division multiple access systems with Markovian spreading sequences. The established analysis with piecewise constant approximation is similar to the mean field analysis which estimates macroscopic characteristics of a spatially-distributed probabilistic system from the local interaction between the elements of the system with low computational complexity. The low complexity makes it possible to analyze the behavior of not only second-order archetype delay-locked loops but also higher-order non-coherent delay-locked loops in the presence of both multiple access interference and channel noise. It is found from the presented analysis that replacing i.i.d. spreading sequences with Markovian spreading sequences with non-vanishing negative autocorrelation reduces the phase tracking error of a non-coherent 1Δ delay-locked loop. The time spent for estimating the error by the presented method is about 1/1000 compared with that by the path integral method.

Due to the broad bandwidth nature of the direct sequence spread spectrum (DSSS) signal, the application of narrowband interference (NBI) cancelation algorithms based on the Nyquist‐Shannon sampling theory are limited by the high sampling rate. To solve the sampling and processing difficulty in the traditional DSSS communication interference cancelation method, we used the compressive sensing (CS) to reduce the sampling rate of the DSSS communication system, and further proposed a compressed domain NBI elimination method in this study. We proved that NBI with a certain bandwidth and DSSS signal are both sparse in specific dictionaries and proposed the corresponding sparse dictionary construction method. Detailed analysis of the compressed domain features of NBI and the DSSS signal demonstrated that it is possible to extract the strong NBI components from the compressed measurements. Two compressed domain NBI cancelation algorithms were proposed based on this idea. The extracted NBI components were filtered out from the compressed measurements directly in the first algorithm, and then we achieved the DSSS signal demodulation in compressed domain using the separated DSSS signal components with the orthogonal matching pursuit (OMP) algorithm. A proposed extraction filter block sparse Bayesian learning (EFBSBL) framework algorithm was utilized to estimate the NBI from the compressed measurements in the second algorithm. The estimated NBI was eliminated from the received signal, and then we recompressed the DSSS signal after NBI cancelation and realized the DSSS signal demodulation in compressed domain with the OMP algorithm. Simulation results support our theoretical analysis results and reveal that the two proposed algorithms are both effective for NBI cancelation and significant interference cancelation performance are achieved.

According to the demand of spread spectrum signal processing in lower SNR conditions, a novel blind estimation algorithm of the pseudo-noise (PN) sequence for the direct sequence spread spectrum (DSSS) signal is proposed based on the similarities among the DSSS signals and the eigenanalysis technique. At first, through segmentation processing and average cross-correlation calculation, the starting symbol of PN sequence is determined. Next, by utilizing the eigenanalysis technique PN sequence can be estimated accurately without any information of the DSSS signal. Simulation results show that compared with the existing algorithms under the same condition, the proposed algorithm not only overcomes the partial-encode problem, but also improves estimation performance by 2dB. Therefore, the proposed algorithm achieves an accurate estimation of PN sequence in lower SNR conditions.

In this paper, we investigate the possibility of improving the blind detection performance of direct sequence spread spectrum (DSSS) signals for cognitive radios (CRs). We consider a scenario where a wide range of frequency spectrum needs to be monitored by a single CR, and the presence of spread spectrum signals need to be identified reliably in a cost effective manner. We employ compressive sensing to achieve realistic sensing time without imposing excessive sampling-rate requirements on the analog-to-digital converter of the CR. We assume that the number, the center frequencies, and the spreading codes of the DSSS signals are unknown, but only the spread signal's bandwidth is known. We propose a three-step algorithm for the CR. First, the power spectral density (PSD) of the wideband spectrum is estimated using compressed samples, and then detection is performed by thresholding to detect spectrum occupancy based on the estimated PSD. In the third step, knowledge of the spread signal's bandwidth, and the estimated PSD are used to perform fusion by looking at spectrum occupancy at adjacent frequency bins using a sliding window. We present some simulation results illustrating the performance gain in detection achieved by introducing the fusion step. This is a useful result since it allows us to detect with improved performance the presence of multiple DSSS signals distributed over a very wideband spectrum, without requiring the knowledge of each signal's spreading code.

Soft synchronization of direct sequence spread spectrum (DSSS) signals introduces the capability of despreading the signals with improving estimates of the spreading code. The technique presented here exploits the eigenstructure of a frequency-channelized DSSS signal to estimate the code. The estimate improves steadily with time, resulting in an improving estimate of the message signal. This allows commencement of despreading at an early stage when the code-estimate is still imperfect. This paper presents the development of the algorithm for a single user environment under infinite time-average assumptions. The performance of the technique under finite time-average conditions is demonstrated through computer simulations for single user as well as multi-user environments.

The conventional hybrid search algorithm for direct sequence spread spectrum (DSSS) signal acquisition terminates once a decision variable exceeds the detection threshold. Therefore, a spurious “hit” declared before the search reaches the cell where the target signal is located avoids any possibility of a correct detection. This behavior increases the probability of false detection, especially in abnormal scenarios, such as when in the presence of interfering signals. To improve the probability of correct detection under a constant false-alarm rate criterion, this paper proposes an advanced hybrid acquisition scheme, whose search area is extended to the whole Doppler frequency and code phase delay uncertainty region. To reduce the mean acquisition time (MAT) increment resulting from this increased search area, both parameters of a Tong detector and the detection threshold are adaptively customized, according to a signal-to-noise ratio estimate obtained during the search operation. In addition, analytic expressions for the detection probability and false-alarm probability are derived. The most prominent advantage of the proposed method is that it can reduce the false detection probability noticeably, with little increase in resource utilization, and an acceptable MAT. The validity of this algorithm is verified, both theoretically and through simulation. The proposed algorithm is particularly suitable for DSSS signal acquisition when in the presence of either multiple access interference or continuous wave interference.

W399 the development of underwater acoustic communications (UWAC), jamming methods for UWAC becomes much more attentive in communication countermeasure system. Direct sequence spread spectrum (DSSS) signal as a way of reliable covert communications is widely used for UWA channels. In this paper, single-tone jamming, narrowband jamming and correlated jamming based on PN code PSK modulation for UWA DSSS communication system are compared under different signal-to-noise ratio first, which assumes that the jammer knows perfect parameters in DSSS signal. Besides, performance of the above three jamming methods are compared by simulations under the blind estimates of carrier frequency, chip length, period of PN code and PN code itself, which demonstrates the influence of the estimation error on these jamming methods.

In this paper, we consider the problem of Doppler tracking and compensation for a direct sequence spread spectrum (DSSS) signal in underwater acoustic (UWA) communication. Since the dynamic property of the UWA channel and the long duration of DSSS signals result in significant Doppler spread that severely distorts the propagated signal, Doppler tracking and compensation are required. Based on the ultra-wideband property of UWA signal, the Doppler spread not only results in the frequency shift, but also changes the signal duration. Therefore, the accurate estimation of the signal expansion/compression in the time domain can reflect the Doppler spread. Accordingly, we present a Doppler tracking and compensation algorithm for a DSSS signal operating on the correlation output of passband signal at a symbol-by-symbol basis. Note that the carrier frequency of UWA communication is around several kilohertz, and thus the time delay estimation can be performed on the passband to improve the accuracy. Furthermore, the prior information of Doppler limit is used to refine the resolution of delay estimation and achieve sequential estimation. To compensate the correlation magnitude distortion induced by the velocity variation, the local reference signal is selected adaptively based on the filtered Doppler factor. Simulation results demonstrate that the proposed passband Doppler tracking algorithm achieves a superior performance compared with the conventional receiver.

A new adaptive estimator for direct sequence spread spectrum (DSSS) signals using fourth-order cumulant based adaptive method is considered. The general higher-order statistics may not be easily applied in signal processing with too complex computation. Based on the fourth-order cumulant with 1D slices and adaptive linear filters, an efficient algorithm is proposed to solve the problem and extended for non-stationary stochastic processes. In order to achieve accurate parameter estimation of direct sequence spread spectrum (DSSS) signals, the first step uses the modified fourth-order cumulant to reduce the computing complexity. While the second step employs an adaptive recursive system to estimate the power spectrum in the frequency domain. For the case of intercepted signals with enough large data samples, the estimator provides good performance in parameter estimation and the white Gaussian noise suppression. Computer simulations are included to corroborate the theoretical development with different signal-to-noise ratio conditions and iterative coefficients.

Complementary coded code-division multiple access (CC-CDMA) system offers many attractive features over traditional CDMA systems due to its potential to provide ideal correlation properties and interference resistance feature in multiuser communication. However, the presence of multiple access interference (MAI) is one of the main drawbacks in reducing system performance under frequency-selective fading channels. In this paper, time domain pre-equalization (TDPE) is considered for downlink CC-CDMA systems to resist MAI over frequency-selective fading channels with perfect knowledge of channel state information. Pre-equalization shifts the complicated signal processing to the base station reducing the receiver complexity and improving the battery lifetime at the mobile station. We perform a comparison study between multiple-input multiple-output CC-CDMA (MIMO CC-CDMA) with pre-equalization and traditional equalization schemes towards overcoming MAI. The comparison study revealed that TDPE at the transmitter enriches diversity gain and reduces MAI in MIMO CC-CDMA systems with less receiver complexity.

Direct-Sequence Spread Spectrum (DS-SS) signals are widely used in modern communications. The detection and parameter estimation of DS-SS signals in non- cooperative context have been paid many attentions. Up to now, most of the proposed methods consider only short-code DS-SS signals, and long-code DS-SS signals have hardly any been studied. In this paper, a method for blind estimation of the symbol period of a long-code DS-SS signal is proposed. The proposed method is based on further processing of the autocorrelation estimator. Simulation results are provided to illustrate the approach.

The complex electromagnetic environment will limit the efficacy of communication equipment. It is critical to construct a complex electromagnetic environment to test communication equipment in order to maximize its capability. One of the most important methods for constructing a complex electromagnetic environment is signal reconstruction. This paper proposes a VAE‐GAN‐based method for reconstructing direct sequence spread spectrum (DSSS) signals. In this method, the deep residual shrinkage network (DRSN) and self‐attention mechanism are added to the encoder and discriminator of VAE‐GAN. In feature learning, the DRSNs can reduce the redundant information caused by noise in the collected signal. The self‐attention mechanism can establish the long‐distance dependence between the input sequences, making it easier for the network to learn the samples’ pseudonoise (PN) sequence features. In addition, feature loss is applied to the encoder and generator to improve network stability during training. The results of the experiments indicate that this method can reconstruct DSSS signals with the characteristics of the target signal.

<p>Fiber-wireless (Fi-Wi) access fronts can support 100s of Mb/s envisioned by 4G networks. However, a major issue associated with Fi-Wi links is the nonlinear distortion of the radio-over-fiber (ROF) link coupled with the multipath dispersion of the wireless channel. Estimation and subsequent equalization of the concatenated fiber-wireless channel needs to be done, especially at high bit rates. The uplink is severely affected due to large fluctuations in the radio signal. This paper proposes an estimation and subsequent equalization algorithm for the Fi-Wi CDMA uplink. The estimation employs the properties of pseudo noise (PN) sequences and the equalization uses a novel Hammerstein type decision feedback equalizer (HDFE). The estimation and equalization are performed in the presence of multiple access interference (MAI) and wireless and optical channel noise. The cumulative effects of multiuser interference, multipath dispersion, nonlinear distortion, and noise are all considered in our analysis. Correlation properties of white-noise like PN sequences enable decoupling of the linear (wireless) and nonlinear (optical) channel portions. Furthermore, we propose a unique algorithm to mitigate MAI. Numerical evaluations show a good estimation and equalization of both the linear and nonlinear channels. Bit error rate (BER) simulations show that this algorithm leaves only small residual MAI.</p>

A minimum mean-squared error (MMSE) linear correlation receiver has been presented to efficiently suppress multiple access interference (MAI) for direct-sequence code-division multiple-access (DS/CDMA) systems in Gaussian channels. The MMSE linear receiver is near-far resistant so as to reduce the requirement of perfect power control. However, additive non-Gaussian impulsive noise bursts in the realistic communication channels. In this paper, we analyze the performance of a linear correlation receiver operating in the presence of MAI and the ambient noise modeled as a symmetric stable process. We also use the Fourier-Bessel series expansion to approximate the exact form of performance analysis. The learning curves of an adaptive linear correlation receiver with different training methods are then examined by computer simulations.

One of the major advantages of a code division multiple access (CDMA) system is the flexibility in frequency assignment, which allows all the users to share the same frequency band and, possibly, to partially overlay the spectrum allocation of different services. However, before synchronism to the desired sequence is achieved, the presence of multiple access interference (MAI) is a major impairment which determines the performance of the code acquisition sub-system. It has been argued that the acquisition performance in the presence of MAI may pose limits to the capacity of a CDMA system which are more stringent than those coming from bit error probability specifications. We introduce a general definition for acquisition-based capacity of a CDMA system. This quantity is evaluated for an acquisition sub-system with non-coherent correlator/detector and straight serial search in the time uncertainty region. The effect of imperfect power control is also analysed, showing that the capacity may be substantially decreased when the residual standard deviation of the received power level is above 1 dB. >