Autocorrelation Properties Research Articles

Random access sequence set design in wireless cellular communication networks

In modern wireless cellular communication systems, Zadoff–Chu (ZC) sequences have been chosen as random access sequences due to their perfect autocorrelation and cross-correlation properties. However, the orthogonality between these sequences is no longer true when there is a frequency offset between the access device and access point. Thereby, the overall performance of ZC sequence-based random access signals will be limited. In this paper, we give a comprehensive analysis on the effect of frequency offset. We show how frequency offset affects the orthogonal property between sequences, and hence incurs the “energy attenuation” and “energy leakage” problems. Consequently, the detection probabilities of the transmitted random access sequences and the false alarm probabilities of the unsent sequences are affected. A frequency offset resistant detection metric is proposed in this paper to improve the detection probability. In order to resist the frequency offset effect as well as apply to the proposed detection metric, mathematical properties of the optimized roots and cyclic shift set are exploited. Finally, we illustrate how to construct a practical random access signal set under the given timing and frequency offset uncertainties. This analytical framework provides a useful insight into ZC sequence-based random access signal design and performance analyses in wireless cellular communication systems.

Accurate Analysis of Implicit SISO Channel Estimation Without DC Offset Using ZCZ Training Sequence

In this letter, an accurate analysis of implicit single-input single-output (SISO) channel estimation is provided. The appropriate correlation properties of the training sequence that result in a closed form solution for the variance of the channel estimate were derived. Indeed, it was shown that only a specific zone in the autocorrelation of the training sequence needs to be equal to zero. As a result, it is now possible to find sequences that simultaneously satisfy the balance and autocorrelation property. In fact, only a special type of sequence called zero correlation zone (ZCZ) sequences have this property and therefore can be used to provide an optimal implicit channel estimation performance when the channel length is inside the zero zone. In addition, by using balanced ZCZ sequences, the harmful Direct Current (DC) offset can be directly removed. Consequently, balanced ZCZ sequences greatly simplifies the implementation of the implicit channel estimation method.

Conjugate Augmented Decoupled 3-D Parameters Estimation Method for Near-Field Sources

A near-field source localization method is proposed for 2-D direction-of-arrival (DOA) and range estimation based on a symmetrical cross array. It first employs the conjugate symmetry property of signal autocorrelation for different time delays to construct a conjugate augmented spatial–temporal cross-correlation matrix, then the extended steering vector is decoupled to avoid the usual multidimensional search based on the properties of the Khatri–Rao product, and finally three 1-D MUSIC-type searches are employed to obtain the results. The proposed method can realize automatic pairing of multiple parameters associated with each source and it also works in the underdetermined case. Furthermore, the stochastic Cramer–Rao lower bound with different time delays is derived. Compared with two existing methods, simulation results demonstrate that the proposed method provides satisfactory estimation performance for both the DOA and range parameters at low signal-to-noise ratio and with a small number of snapshots.

Non-Binary PRN-Chirp Modulation: A GNSS Fast Acquisition Signal Waveform

In this letter, we propose a new non-binary modulation which allows both Global Navigation Satellite Systems (GNSS) synchronization and the demodulation of non-binary symbols, without the need of a pilot signal, with the aim to provide a fast first position, velocity and time fix. The waveform is constructed as the product of i) a pseudo-random noise sequence with good auto-correlation and cross-correlation properties, and ii) a chirp spread spectrum family, which allows to demodulate non-binary symbols even if the signal phase is unknown. In order to demodulate the data, a bank of non-coherent matched filters is proposed. Because of the particular modulation structure, the receiver is capable to demodulate the navigation message faster while allowing the basic GNSS signal processing functionalities. Illustrative results are provided to support the discussion.

Global temporal typing patterns in foreign language writing: exploring language proficiency through recurrence quantification analysis (RQA)

Recurrence quantification analysis (RQA) is a time-series analysis method that uses autocorrelation properties of typing data to detect regularities within the writing process. The following paper first gives a detailed introduction to RQA and its application to time series data. We then apply RQA to keystroke logging data of first and foreign language writing to illustrate how outcome measures of RQA can be understood as skill-driven constraints on keyboard typing performance. Forty native German students performed two prompted writing assignments, one in German and one in English, a standardized copy task, and a standardized English placement test. We assumed more fluent and skilled writing to reveal more structured typing time series patterns. Accordingly, we expected writing in a well-mastered first language to coincide with higher values in relevant RQA measures as compared to writing in a foreign language. Results of mixed model ANOVAs confirmed our hypothesis. We further observed that RQA measures tend to be higher, thus indicating more structured data, whenever parameters of pause, burst, and revision analyses indicate more fluent writing. Multiple regression analyses revealed that, in addition to typing skills, language proficiency significantly predicts outcomes of RQA. Thus, the present data emphasize RQA being a valuable resource for studying time series data that yields meaningful information about the effort a writer must exert during text production.

Quality-Relevant Process Monitoring with Concurrent Locality-Preserving Dynamic Latent Variable Method.

A concurrent locality-preserving dynamic latent variable (CLDLV) method is proposed to extract the correlation between process variables and quality variables for quality-related dynamic process monitoring. Given that dynamic process data can easily be contaminated by noise and outliers and conventional dynamic latent variable models lack robustness, a low-rank autoregressive model is developed to deal with autocorrelation and cross-correlation properties among the data. Then neighborhood structure information is integrated into the partial least squares model, which can better reveal the essential structure of the data. The final concurrent projection of the latent structures is employed to monitor output-related faults and input-related process faults that affect quality. The Tennessee Eastman process and hot strip mill process are used to demonstrate the effectiveness of CLDLV-based detection and diagnostic methods.

Macroeconomic risk factors and REITs returns predictability in African markets: Evidence from a new approach

This study examines the predictability of REITs returns considering the role of macroeconomic risk predictors for three emerging African REITs markets, namely Ghana, Nigeria and South Africa. To account for the inherent statistical properties of persistence, endogeneity, autocorrelation and conditional heteroscedasticity, we apply the Feasible Quasi Generalized Least Squares (FQGLS) estimator. In addition, the role of asymmetries is considered. Our findings show the heterogeneous performance of the risk factors. All the risk predictors matter in predicting REITs returns in a non-linear fashion in Nigeria, while asymmetries appear to matter only for both interest rate and exchange rate in Ghana, and only interest rate in South Africa. These results suggest that the predictors are important forecast factors for the REITs market. Taking a step further to examine and compare their forecast performance with the traditional model, we find that the macroeconomic risk factors-based predictive model outperforms the traditional ARFIMA model in several cases in the countries, especially Nigeria. Robustness is provided for these results through the use of different sample periods and forecast horizons. Notable policy implications for investors and portfolio managers can therefore be derived from these findings.

Some new classes of quaternary sequences with low autocorrelation property via two binary cyclotomic sequences

Some new classes of quaternary sequences with low autocorrelation property via two binary cyclotomic sequences

Effects of spatial variability of soil properties and ground motion characteristics on permanent displacements of slopes

The seismic performance of earth slopes is a problem of great importance in geotechnical earthquake engineering associated with various sources of uncertainty. This research investigates the effects of two important causes of such uncertainty: (a) the spatial variability of soil properties and (b) the variability of the temporal and frequency characteristics of the earthquake excitation. The former is investigated based on a series of detailed dynamic numerical simulations using stationary random fields of both cross-correlated and spatially autocorrelated soil properties. The latter is explored by conducting incremental dynamic analysis at various levels of excitation intensity using (a) a total of forty historic earthquake and synthetic records, modified to match the Eurocode 8 design spectra for rock sites, and (b) thirty original historic earthquake records. The results demonstrate the significant effect of the spatial variability of soil properties on the permanent slope displacements. Moreover, they show that the effect of the uncertainty associated with the variability in the temporal and frequency characteristics of excitations is more important compared to the effect of the spatial variability of soil properties.

Quantum statistics engineering in a hybrid nanoparticle-emitter-cavity system

Quantum engineering of photons is a key requirement for the development of quantum technology. Here, we put forward a scheme to investigate extensively quantum statistical characteristics of the photons and their engineering in a hybrid nanoparticle-emitter-cavity architecture through placing a nanoparticle (NP) and a quantum emitter (QE), called NP-QE molecule, into an optical cavity, where the coherent tripartite coupling emerges in the interactions among the NP, QE, and cavity. The photons are collected from the two different channels, i.e., the cavity emission and the NP-QE molecule scattering. Due to the composite nature of the tripartite dressed excitations of our fully coupled system and the destructive interference between different transition pathways for the two-photon excitation, the nontrivial quantum statistical properties, such as unconventional single-photon blockade and strong photon superbunching, can be achieved even within the bad cavity limit (without the need of the strong-coupling condition) when the NP-QE molecule is driven by an external laser not interacting the cavity mode. It is also revealed that the photon autocorrelation and cross-correlation properties are well modified by regulating the size-dependent system parameters, such as the NP-to-QE distance and the NP radius. The small-coupling strength required, the ease of parameter tuning, the relaxation of high-cavity quality factor, and the robustness to the dephasing rate in realistic scenarios all benefit the generation of single-photon sources, which has potential applications in quantum information and quantum communication.

Preamble Design Technique for Accurate Timing/Positioning in High Doppler Environments

Accurate estimation of timing is essential for positioning in cellular systems because propagation delays from neighboring base stations are used to calculate the position of a mobile station. A preamble design technique for accurate timing estimation in cellular systems with high mobility, such as autonomous driving and unmanned aerial vehicles, is proposed herein. A generalized Zadoff-Chu (ZC) sequence is defined and decomposed into multiple short subsequences to reduce the Doppler effect on the timing estimation. The performance loss caused by the short sequence length is compensated by combining the subsequences using the repetition property of the ZC sequence. The properties of autocorrelation and cross-correlation of the generalized ZC sequence that employs a receiver processing (RP) scheme (subsequence decomposition and combining) are analyzed in the presence of Doppler. Finally, the suitability of the proposed sequence with the RP scheme, for accurate timing estimation in multicell environments with a high Doppler, is demonstrated using simulation results.

Waveform Design and Performance Analysis for Full-Duplex Integrated Sensing and Communication

Integrated sensing and communication (ISAC) is a promising technology to fully utilize the precious spectrum and hardware in wireless systems, which has attracted significant attentions recently. This paper studies ISAC for the important and challenging monostatic setup, where one single ISAC node wishes to simultaneously sense a radar target while communicating with a communication receiver. Different from most existing schemes that rely on either radar-centric half-duplex (HD) pulsed transmission with information embedding that suffers from extremely low communication rate, or communication-centric waveform that suffers from degraded sensing performance, we propose a novel full-duplex (FD) ISAC scheme that utilizes the waiting time of conventional pulsed radars to transmit communication signals. Compared to radar-centric pulsed waveform with information embedding, the proposed design can drastically increase the communication rate, and also mitigate the sensing eclipsing and near-target blind range issues, as long as the self-interference (SI) is effectively suppressed. On the other hand, compared to communication-centric ISAC waveform, the proposed design has better auto-correlation property as it preserves the classic radar waveform for sensing. Performance analysis is developed by taking into account the residual SI, in terms of the probability of detection and ambiguity function for sensing, as well as the spectrum efficiency for communication. Numerical results are provided to show the significant performance gain of our proposed design over benchmark schemes.

Index Modulation With Circularly-Shifted Chirps for Dual-Function Radar and Communications

In this study, we propose index modulation (IM) with circularly-shifted chirps (CSCs) (CSC-IM) for dual-function radar and communication (DFRC) systems. The proposed scheme encodes the information bits with the CSC indices and the phase-shift keying (PSK) symbols. It allows the receiver to exploit the frequency selectivity naturally in fading channels by combining IM and wideband CSCs. It also leverages the fact that a CSC is a constant-envelope signal to achieve a controllable peak-to-mean envelope power ratio (PMEPR). For radar functionality, CSC-IM maintains the good autocorrelation (AC) properties of a chirp by ensuring that the transmitted CSCs are separated apart sufficiently in the time domain through index separation (IS). We investigate the impact of IS on spectral efficiency (SE) and obtain the corresponding mapping functions. For theoretical results, we derive the union bound (UB) of the block error rate (BLER) for arbitrary chirps and the Cramer-Rao lower bounds (CRLBs) for the range and reflection coefficients for the matched filter (MF)- based estimation. We also prove that complementary sequences (CSs) can be constructed through CSCs by linearly combining the Fourier series of CSCs. Finally, through comprehensive comparisons, we demonstrate the efficacy of the proposed scheme for DFRC scenarios.

Cognitive waveform design with desired spectrum-autocorrelation properties

This paper proposes a novel cognitive waveform design methodology aimed at shaping a specified spectrum and achieving good autocorrelation properties in terms of the spectrum band notch and local autocorrelation peak sidelobe level (A-PSL). To this end, the Pareto optimization framework is introduced that minimizes the lp-norm of multi-objective functions both encompassing the stopband energy and local A-PSL. In addition, along with energy and peak-to-average power ratio constraints to ensure hardware compatibility, the out-of-band (OOB) spectrum energy and the rest autocorrelation sidelobe level are restricted to resist the OOB strong interference (also prevent spectrum leakage) and enhance multiple target detectability, respectively. To tackle the resultant nonconvex nonsmooth (in general NP-hard) design problem, an iterative majorization minimization proximal method of multipliers (MM-PMM) algorithm is developed along with each iteration involving multiple subproblems which are solved through a majorization method or closed-form solutions. In particular, resorting to Wiener-Khintchine theorem, the developed algorithm is efficiently implemented via the fast fourier transform and element-wise arithmetic. Extensive numerical examples highlight that the synthesized waveform shares the desired spectrum-autocorrelation properties and is capable of enhancing the weak target detection and anti-jamming performance in comparison with some counterparts.

Underwater acoustic communication based on chirp spread spectrum with cyclic shifted PN sequences

In this presentation, we propose a new underwater acoustic communication technique that combines a binary PN (Pseudo Noise) sequence to which cyclic shift is applied and a CSS (Chirp Spread Spectrum) method that is robust against low Doppler shift. PN sequences are known to have sharp autocorrelation function and cyclic properties. In the case of the previous CSS method, 1-bit per symbol was mapped according to the sign of the slope in the time-frequency domain of the chirp signal, but the proposed method maps 2-bit per symbol according to the cyclic shift direction of PN sequence and the slope of the chirp. As a result, the transmission data rate is doubled. For example, “00” symbol is expressed as an up-chirp and right cyclic shifted PN sequence, and “11” symbol can be expressed as a down-chirp and left cyclic shifted PN sequence. This combination can have excellent autocorrelation properties and Doppler shift immunity. The performance of the proposed method will be compared with that of the previous method by presenting the results of the sea trial. [Work supported by the Agency for Defense Development, South Korea, Grant No. UD200002DD.]

M-ARY CDMA SCHEME WITH CCSK MODULATION AND PARALLEL INTERFERENCE CANCELLATION TECHNIQUE

In this paper, we tackle the problem of implementation a parallel interference cancellation scheme for multi-user detection (MUD) in M-ary CCSK-modulated CDMA system. Complexity remains the main obstacle to the practical implementation of MUD and a factor limiting, if not the very possibility, then the feasibility of using high order M-ary modulation formats for applications such as low-probability-of-intercept systems with a large spreading factor or, myriads of small self-powered IoT devices. The design of MUD algorithms for M-ary systems leads to a new round of growth in the receiver complexity comparing with the binary modulation. Demodulator has a major impact on the complexity of CDMA system. Cyclic code-shift keying (CCSK) is a modulation technique which is designed to reduce the complexity of M-ary signaling. In this, each symbol is a circularly shifted version of a single code sequence. Assuming synchronization, the receiver cyclically correlates the input signal plus noise with the base sequence and estimates the position of the correlation peak. The preliminary stage of the proposed scheme is a conventional multi-channel CDMA receiver. The preliminary estimates of the data is multiplied by user codes and amplitude estimates in the spreader, and then fed to the adder to generate the MAI estimates. After the latter are subtracted from the group signal, K-dimensional vector of cleared user signals is passed to the matched filter bank to form the refined estimates of the data. At each subsequent stage, the estimates of the output data of the previous stage are used as input data. The complexity gain is the ratio of the number of computations for finding cyclic convolution and, the amount of computations for finding M linear convolutions, i.e., M/log2M. Since the performance of the algorithm is sensitive to the reliability of the preliminary decisions, there are strict criteria for the selection of spreading codes: the length which must be an integer power of 2, the large family size, good periodic autocorrelation and good cross-correlation properties. To examine the proposed algorithm using computer simulation, we selected minimax periodic and odd-periodic complementary codes, the properties of which are close to the properties of the codes used in the CCSK scheme implemented in Link-16 protocol tactical data networks JTIDS and MIDS. Our study shows that the gain over the conventional receiver increases as the SNR increases, achieving 15 dB for BER 10-5. The system with complementary codes outperform system based on minimax PN-codes, achieving a target bit error rate at a lower SNR.

A high frequency endoscopic ultrasound imaging method combining chirp coded excitation and compressed sensing

Insufficient imaging penetration and large data acquisition are two of the major challenges of high-frequency ultrasound imaging. Based on the good autocorrelation properties of chirp signal and the feasibility of using compressed sensing theory to reconstruct high-quality ultrasound images with low sampling requirements, this paper proposed a chirp coded excitation combined with compressed sensing (CCE-CS) technique for high-frequency endoscopic ultrasound (HFEUS) imaging. The feasibility of the method was verified by a brief theoretical analysis, and the relevant parameters were selected and analyzed according to the actual engineering situation. Simulated phantoms and in-vitro tissue experiments were used to evaluate the performance of the CCE-CS. Simulation results demonstrate that CCE-CS is capable of reducing the impact of reconstruction errors and improving imaging quality through comparison with conventional methods. The reduction of reconstruction data had less impact on penetration depth, resolution and general contrast general contrast-to-noise ratio (gCNR), and the reconstructed image was closer to the original image with a maximum improvement of 37% in peak signal-to-noise ratio (PSNR). Moreover, comparisons were conducted on the digestive tract of swine, and the results show that CCE-CS is also feasible in the in-vitro environment. These results demonstrated that CCE-CS method has good potential for application to improve the imaging quality of HFEUS while reducing the sampling rate.

An Interference-Tolerant Synchronization Scheme for Wireless Communication Systems Based on Direct Sequence Spread Spectrum

In this paper, an interference-tolerant three-level synchronization scheme for wireless communication systems based on Direct Sequence Spread Spectrum (DSSS) is presented. Although the proposed synchronization scheme is demonstrated in a mixed signal IC solution, it is exportable to fully digital realizations. The proposed technique synchronizes the received pseudo-random sequence (PRS) modulated signal with the receiver (RX) reference PRS by making use of its autocorrelation properties. The proposed scheme employs 3 levels that make the proposed scheme tolerant to strong in-band interferences. Experimental results for the prototype demonstrate the capabilities of the proposed approach to achieve over 50% of clock cycle tracking even in the presence of interferences with a power of 5dB higher than the desired signal power. Fabricated in a mainstream 40nm CMOS technology, the synchronization scheme employs 100MHz PRS at TX and RX; the proposed solution consumes 18.7mW power and around 0.087mm² silicon area.

COMBINATORIAL OPTIMIZATION OF SYSTEMS OF NEURAL NETWORK CRYPTOGRAPHIC DATA PROTECTION

The problem of improving the reliability of cryptographic data protection in neural network systems with flexible configuration is considered. To ensure the possibility of encrypting/decrypting messages it is proposed to use combinatorial optimization methods for the tasks of forming encoded sequences with improved quality indicators for correcting ability, noise immunity, and autocorrelation properties. The basis of combinatorial optimization is the principle of optimal structural relationships, the essence of which is to achieve the maximum diversity of the system under the established restrictions on the number of structural elements and their mutual placement in space-time. It is proposed to use signal-code sequences for neural network data protection, which are characterized by high noise immunity and low level of the autocorrelation function, using various types of optimized code sequences depending on the set of requirements for work under specific conditions, taking into account restrictions on the duration of sending encrypted messages and the presence of noise in communication channels. The system for neural network cryptographic data protection has been developed using encoded signal sequences, where the number of binary characters of different names differs by no more than one character, which minimizes the value of the autocorrelation function of the encoded signal at a fixed bit depth. To ensure high technical and economic indicators of the cryptosystem, it is advisable to equip it with specialized modules of neuro-similar elements of the network with the possibility of training and flexible configuration for cryptographic data encryption. The relationship between the parameters of optimized encoded signal sequences, in which the value of the autocorrelation function is minimized, and the maximum achievable number of detected and corrected errors has been established. It is proposed to use unique properties of combinatorial configurations with a non-uniform distribution of structural elements, which are distinguished by the fact that the set of all ring sums of their numerical values occurs a fixed number of times. A comparative analysis of cryptographic methods for data protection and transfer using non-standard codes built on the so-called IRB code sequences together with other signal-code constructions was carried out.

On Properties of Periodic Binary Sequences in the Presence of System Non-Linearities

Phase-modulated continuous-wave (PMCW) radar systems possess inherent interference mitigation capabilities and can be useful for many civilian applications including autonomous driving. For PMCW radar systems, binary sequences with good autocorrelation properties are used as probing sequences due to their low cost to generate in practical hardware systems. However, the non-linearity (NL) suffered by practical PMCW radar systems can produce undesirable cross-products and distort the receiver matched filter outputs. The purpose of this paper is to investigate the properties of the well-known periodic binary almost perfect autocorrelation sequences (APAS) under NL conditions, including even-order and odd-order NL conditions. We also consider designing long binary periodic sequences with low autocorrelation sidelobes within a low correlation zone (LCZ) using a computational algorithm. The computationally optimized sequences (COS) do not suffer from sequence length restrictions and offer much higher diversity than their APAS counterparts. We compare COS with APAS under NL conditions. We show that both types of sequences can be used to avoid ghost peaks in the range profiles under NL conditions.