Direct Sequence Spread Spectrum Signals Research Articles

A Semidefinite Relaxation Approach to Spreading Sequence Estimation for DS-SS Signals

SUMMARY In non-cooperative scenarios, the estimation of direct sequence spread spectrum (DS-SS) signals has to be done in a blind manner. In this letter, we consider the spreading sequence estimation problem for DS-SS signals. First, the maximum likelihood estimate (MLE) of spreading sequence is derived, then a semidefinite relaxation (SDR) approach is proposed to cope with the exponential complexity of performing MLE. Simulation results demonstrate that the proposed approach provides significant performance improvements compared to existing methods, especially in the case of low numbers of data samples and low signal-to-noise ratio

A novel unified equalization and demodulation of chaoticdirect sequence spread spectrum signal based on state estimation

A novel unified algorithm based on state estimation was proposed for equalization and demodulation of chaotic direct sequence spread spectrum (CD3S) signal through a non-ideal channel. The algorithm uses the state equations of the channel and the CD3S signal, as well as the reciprocal relationship between equalization and demodulation. Multiple extended kalman filters (EKF) were used for equalizing the channel while demodulating the binary message simultaneously by implementing them in reciprocal interaction. This algorithm could not only overcome the impact brought about by non-ideal channel, such as multipath interference and channel noise, but also demodulate the binary message from CD3S signal. This unified approach utilizes the information more adequately and has better real-time performance than independent approaches. Simulation results demonstrated that the proposed algorithm has a fast convergence rate, and is resistant to the multipath effect without knowledge of channel characteristic and the noise, so the efficient and reliable transmission of the CD3S signal through the non-idea channel is realized.

Breakability of chaotic direct sequence spreading spectrum secure system under multi-path fading channel

Blind demodulation (breaking) of chaotic direct sequence spread spectrum (CD3S) signals is a challenging and leading issue under multipath fading channel in the field of chaotic communication. Until now, there are neither equalization methods to remove the impact of the channel, nor the immediate breaking methods. Based on the existing study, the breakability of CD3S signals is analyzed under multipath fading channel by using unscented Kalman filter (UKF) chaotic fitting in this paper. Beginning with the state space equation for the CD3S signals in UKF chaotic fitting, the channel influence on the tracking error is analyzed in the process of UKF chaotic fitting, then the range of the message state estimation is derived, and finally a sufficient condition theorem is proposed for the CD3S signals to be broken. Simulation results show that CD3S signals can be broken successfully under the proposed condition with excellent performance of bit error rate (BER), no matter whether the channel characteristic is either time-invariant or time-variant.

A Unified Framework for Interference Analysis of Noncoherent MFSK Wireless Communications

This paper presents a new unified analytical technique for accurate interference analysis of noncoherent M-ary frequency shift keying (MFSK) wireless communication systems in the presence of additive white Gaussian noise (AWGN) and multiple arbitrary interfering signals. New exact bit error rate expressions are derived for nonorthogonal noncoherent binary FSK in the presence of an arbitrary number of interfering signals having arbitrary spectral shapes at arbitrary frequency offsets. Furthermore, tight upper bounds for the symbol and bit error rates are given for noncoherent MFSK with arbitrary tone spacings. These results are extended to include MFSK signals experiencing Rayleigh, Nakagami-m or Rician fading. Some specific interference scenarios are analyzed in details, including jammers with a given Doppler-spread, direct sequence spread spectrum and orthogonal frequency division multiplexing signals, and a Poisson field of arbitrary interferers.

Despreader for direct sequence spread spectrum system and its performance analysis

A new type of despreader for direct sequence spread spectrum signal is proposed. Compared with traditional despreaders, the new despreader does not contain hard decision ware or handle binary sequence any more, and the locally stored spread spectrum signals are pre-modulated baseband signals (such as Gaussian minimum shift keying (GMSK) signals), which are much more similar to the received spread spectrum signals. Moreover, the missed detection probability of the despreader is about one order of magnitude lower than that of traditional ones. Based on the maximum likelihood criterion and phase probability density function of demodulated signal, a new method of analyzing the despreaders’ performance is put forward, which is proved to be more accurate than traditional methods according to the numerical results. Finally, an adaptive despreader under different signal-to-noise ratios is given.

A PN sequence estimation algorithm for DS signal based on average cross-correlation and eigenanalysis in lower SNR conditions

According to the demand of spread spectrum signal processing in lower SNR conditions, a novel algorithm for blind estimation of the pseudo-noise (PN) sequence of the direct sequence spread spectrum (DSSS) signal is proposed based on the similarities among the DSSS signals and the eigenanalysis technique. Firstly, through segmentation processing and average cross-correlation calculation, the starting symbol of PN sequence is determined. Then, by utilizing the eigenanalysis technique PN sequence can be estimated accurately without any information of the DSSS signal. By theoretical analysis and logical deduction, two conclusions about the estimation efficiency and estimation error between the proposed algorithm and the existing algorithms are presented and proved. 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 2 dB, which indicates that the proposed algorithm achieves an accurate estimation of PN sequence in lower SNR conditions.

Performance evaluation of detection of Direct Sequence Spread Spectrum signals over a flat fading channel

Performance evaluation of detection of Direct Sequence Spread Spectrum signals over a flat fading channel

Performance Analysis of a Complex Multicode Tracking Loop in Bandlimited Rayleigh Fading Channels

This paper presents the root-mean-squared tracking error performance analysis of a class of coherent digital delay-locked loops for multicode direct sequence spread spectrum signals in bandlimited correlated Rayleigh fading channels. In the transmit side, multiple independent PSK-modulated data streams in the in-phase and qudrature phase branches are spread by short mutually orthogonal codes before being further complex spread by a long complex PN code. We assume that the system employs a pilot code channel to assist the receiver's synchronization and channel estimation. The proposed code tracking loop incorporates the pilot-aided channel estimator and derives the timing error from all short-code-spread subchannels. Our analysis takes into account the effects of imperfect channel estimate, correlated frequency selective Rayleigh fading and band-limiting. Numerical results are presented to quantify the impact of the resulting multipath interference within the same code channel and amongst different code channels.

Blind classification of the short-code and the long-code direct sequence spread spectrum signals

Direct sequence spread spectrum (DSSS) signals are now widely used for communications. According to the relationship between spreading factor and code length, the DSSS signals can be divided into two types: the short-code (SC) and the long-code (LC) DSSS. For the cooperative receivers, the above type information is known in advance. However, under the non-cooperative contexts, such information becomes one of the unknown parameters of interest. To extract this information, a blind algorithm that is based on the second-order statistics of the matrix norms of the signal correlation matrices is proposed in this study. A set of correlation matrices is constructed from the received signal samples following which the matrix norm of each correlation matrix is computed and normalised by the maximum. Then, by comparing the variance of the normalised matrix norms with a preset threshold, the type of the received DSSS signal can be identified. Simulation results verify the capability of the proposed method in various scenarios, such as multipath fading channel and multiple access interference.

Invariant detection for short-code QPSK DS-SS signals

This paper focuses on the optimal detection of quadrature phase-shift keying (QPSK) direct sequence spread spectrum (DS-SS) signals in additive white Gaussian noise (AWGN) with unknown parameters. We consider the invariant detection problem using the complex Gaussian mixture and the modulo-shift signal model, and derive constant-false-alarm-rate (CFAR) invariant detectors such as uniformly most-powerful invariant (UMPI) test and other sub-optimal invariant tests such as the generalized likelihood ratio test (GLRT). An approximation of the UMPI test under low signal-noise-ratio scenarios yields an asymptotic locally most-powerful invariant (ALMPI) test, which has similar computational complexity as the cycle feature detectors. The ALMPI test is computationally efficient compared with the UMPI and GLRT tests. Moreover, further approximation to the ALMPI test leads to the incoherent weighted multi-cycle detectors, which serve as the performance upper bound of all the spreading sequence period detectors based on second-order cyclostationary statistics. Simulation results demonstrate that the proposed ALMPI test exhibits better detection performance than cycle feature detectors with finite observation samples.

Criteria to Improve Time-Delay Estimation of Spread Spectrum Signals in Satellite Positioning

Positioning accuracy in satellite navigation systems depends on time-delay estimation (TDE) between satellite transmitted codes and local receiver replicas. This paper explores the fundamental limits of TDE accuracy of spread spectrum signals making use of estimation theory. In particular, this contribution derives some criteria to improve positioning accuracy in the additive white Gaussian noise (multipath-free) scenario, focusing on the (satellite) transmitter side of a direct sequence spread spectrum (DS-SS) system. Three different solutions based on the minimization of the variance of the TDE are presented. The first method derives a design criterion for the shaping pulse format. The second approach outlines a method to design binary pseudorandom spreading sequences. The third solution considers a joint shaping pulse-spreading code optimization to derive band-limited, non-binary spreading waveforms. Performance of the proposed solutions is compared with that of existing DS-SS signals for current satellite positioning systems. Possible countermeasures to the effects of multipath propagation are also discussed.

Spectrally Shaped DS–CDMA with Dual Sideband Combining for Increased Diversity on Dispersive Fading Channels

A new modulation scheme is proposed in this paper. This scheme uses sinusoidal chip waveforms to shape the spectrum of a direct sequence spread spectrum (DS-SS) signal such that the transmitted signal has two distinct spectral lobes, one from a lower sideband (LSB) and the other from an upper sideband (USB). By properly selecting the frequency of the sinusoidal chip waveforms, the two sideband signals can be made to undergo independent fading in a dispersive fading channel. These two independent sideband signals, when combined at the receiver, provide diversity gain. Our analysis and simulation results show that the bit error ratio (BER) performance of the proposed scheme is superior to that of the equivalent DS-SS system that uses conventional rectangular chip waveforms for severely faded channels.

Time-Frequency Channel Parameterization with Application to Multi-Mode Receivers

There is a trend towards flexible radios which are able to cope with a range of wireless communication standards. For the integrated processing of widely different signals—including single-carrier, multicarrier, and spread-spectrum signals—monolithic baseband receivers need universal formats for the signal representation and channel description. We consider a reconfigurable receiver architecture building on concepts from time-frequency (TF) signal analysis. The core elements are TF signal representations in form of a Gabor expansion along with a compatible parameterization of time-variant channels. While applicable to arbitrary signal types, the TF channel parameterization offers similar advantages as the frequency domain channel description employed by orthogonal frequency-division multiplexing receivers. The freedom in the choice of the underlying analysis window function and the scalability in time and frequency facilitate the handling of diverse signal types as well as the adaptation to radio channels with different delay and Doppler spreads. Optimized window shapes limit the inherent model error, as demonstrated using the example of direct-sequence spread-spectrum signaling.

Multichannel direct sequence spectrum signaling using code phase shift keying

In this paper, we have designed and realized multichannel direct sequence spread spectrum (DSSS) system using code phase shift keying (CPSK). In the transmitter, taking each bit from each channel, data word is made as a symbol for selecting PN sequence, which is modulated with frequency of 100 MHz as DSSS signals. At the receiver, the correlator, integrator and decoder are used for separation of the signal of respective channel after demodulation. Oscilloscope traces show that the transmitted signals are matched with the simulated signals at the receiver. The bit error rate (BER) variation with jamming signal is estimated by our proposed simulation model, matching well with experimental values of BER measured by BER meter.

Experimental validation of a chirp-based underwater acoustic communication method

A wireless underwater acoustic communication algorithm based on the combination of chirp modulation and direct-sequence spread-spectrum signaling is presented. In this paper, the processing chain design is proposed, discussed, and demonstrated using real data. The communication algorithm is made of a transmission block encoding the bits with adequate linear chirps multiplied by pseudo noise (PN) sequences, and a rake receiver that allows one to positively exploit the energy present in the most significant propagation paths. The use of chirp signals takes advantage of the low Doppler sensitivity in the matched filter operation whereas the choice of PN sequences allows one to reduce narrowband interference arising from other users and self-interference due to multipath propagation. Moreover a tracking procedure that allows an adaptation to the instantaneous Doppler shift has been devised and tested. Some experiments have been carried out changing the distance and the speed between transmitter and receiver. Results show that the developed communication method is able to handle the multipath phenomenon and the Doppler effect, allowing one to achieve a bit error rate less than 10 (-3) for long ranges for bit rates of about 15 and 230 bit/s.

Spectrally shaped generalized MC-DS-CDMA with dual band combining for increased diversity

A new multicarrier spread spectrum modulation scheme is proposed in this paper. This scheme uses sinusoidal chip waveforms to shape the spectrum of each subcarrier of a multicarrier direct sequence spread spectrum (DS-SS) signal. As a result, each subcarrier has two distinct spectral lobes, one a lower sideband (LSB) and the other an upper sideband (USB). By properly selecting the parameters of the sinusoidal chip waveforms, the two sideband signals can be made to undergo independent fading in a dispersive fading channel. These two independently-faded sideband signals, when combined at the receiver, provide diversity gain to the system. Our analysis and simulation results show that by properly selecting the chip waveform parameter and the intersubcarrier frequency separation, the bit error ratio (BER) performance of the proposed scheme is superior to that of the conventional MC-DS-CDMA system in dispersive fading channels. In addition, spectral sidelobes are naturally reduced by our scheme.

Anti-Interference Receiver Structures for Direct Sequence Spread Spectrum Signals

Conventional narrowband interference (NBI) rejection algorithms often assumed perfect pseudo-noise (PN) code synchronization. The functions of NBI rejection and code tracking are performed separately and independently by an adaptive filter and a code tracking loop, respectively. This paper presents two new receiver structures for direct sequence spread spectrum (DS/SS) systems, one operates in coherent mode and the other operates in noncoherent mode. Both receivers are designed to suppress NBI and minimize tracking jitter. Numerical results show that the proposed coherent receiver performs as good as the conventional receiver that uses an LMS NBI rejection filter with zero tracking jitter. The noncoherent receiver, when compared with the coherent one, suffers less than 3dB degradation for bit error probability smaller than 10-3.

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[ y iy 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.

Performance analysis of direct-sequence spread-spectrum underwater acoustic communications with low signal-to-noise-ratio input signals

Direct-sequence spread-spectrum signals collected from the TREX04 experiment are analyzed to determine the bit-error-rate (BER) as a function of the input signal-to-noise ratio (SNR) for a single receiver. A total of 1160 packets of data are generated by adding ambient noise data collected at sea to the signal data (in postprocessing) to create signals with different input-SNR, some as low as -15 dB. Two methods are analyzed in detail, both using a time-updated channel impulse-response estimate as a (matched) filter to mitigate the multipath-induced interferences. The first method requires an independent estimate of the time-varying channel impulse-response function; the second method uses the channel impulse-response estimated from the previous symbol as the matched filter. The first method yields an average BER <10(-2) for input-SNR as low as -12 dB and the second method yields a similar performance for input-SNR as low as -8 dB. The measured BERs are modeled using the measured signal amplitude fluctuation statistics and processing gain obtained by de-spreading the received signal with the transmitted code sequence. Performance losses caused by imprecise symbol synchronization at low input-SNR, uncertainty in channel estimation, and signal fading are quantitatively modeled and compared with data.

Improved blind-spreading sequence estimation algorithm for direct sequence spread spectrum signals

Direct sequence spread spectrum (DSSS) signals are now widely used for communications. DSSS transmitters use a spreading sequence to modulate the baseband signal before transmission. A receiver which does not know the spreading sequence cannot demodulate the signal. Burel and Bouder introduced an eigenanalysis-based blind-spreading sequence estimation algorithm, which performs well even when the received signal is far below the noise level. However, this algorithm does not applied to the long-code DSSS signals. An improved blind-spreading sequence estimation algorithm is presented. This algorithm is based on segmentation. The received signal is divided into K collections of temporal windows, from which K covariance matrices can be computed. The authors prove that K short-time segments of the spreading waveform can be recovered from these matrices using the eigenanalysis technique. Then, the spreading sequence can be reconstructed by concatenating these short-time segments. Simulations show that the proposed algorithm can provide a good estimation for long- or short-code DSSS signals in non-cooperative context, even with low signal-to-noise ratio. Furthermore, for short-code DSSS signals, the computational cost of the proposed algorithm is much lower than that of the original algorithm.