This paper proposes a new approach for generating pseudo random multi-valued (including binary-valued) sequences. The approach uses a primitive polynomial over an odd characteristic prime field $\f{p}$, where p is an odd prime number. Then, for the maximum length sequence of vectors generated by the primitive polynomial, the trace function is used for mapping these vectors to scalars as elements in the prime field. Power residue symbol (Legendre symbol in binary case) is applied to translate the scalars to k-value scalars, where k is a prime factor of p-1. Finally, a pseudo random k-value sequence is obtained. Some important properties of the resulting multi-valued sequences are shown, such as their period, autocorrelation, and linear complexity together with their proofs and small examples.

In this paper, we propose a framework to allocate code rates of component codes in a Plotkin-type unequal error protection (UEP) code. We derive an equivalent noise variance for each component code using structure of the Plotkin construction and Gaussian assumption. Comparing the equivalent noise variance and Shannon limit, we can find a combination of the code rates for the component codes. We investigate three types of code rate combinations and analyse their UEP performance. We also estimate a performance crossing signal to noise ratio (SNR) of the Plotkin-type UEP code. It indicates that which code has better performance for a given SNR. We confirm that the proposed framework is appropriate to obtain a desired UEP capability.

In this paper, we examine the locality property of the original Fractional Repetition (FR) codes and propose two constructions for FR codes with better locality. For this, we first derive the capacity of the FR codes with locality 2, that is the maximum size of the file that can be stored. Construction 1 generates an FR code with repetition degree 2 and locality 2. This code is optimal in the sense of achieving the capacity we derived. Construction 2 generates an FR code with repetition degree 3 and locality 2 based on 4-regular graphs with girth g. This code is also optimal in the same sense.

In conventional spread spectrum (SS) watermarking schemes, random sequences are used for the modulation of watermark information. However, because of the mutual interference among those sequences, it requires complicated removal operation to improve the performance. In this paper, we propose an efficient spread spectrum watermarking scheme by introducing the orthogonal frequency divisiion multiplexing (OFDM) technique at the modulation of watermark information. The SS sequences in the proposed method are the DCT basic vectors modulated by a pseudo-random number (PN) sequence. We investigate the SS-based method considering the host interference at the blind detection scenario and analyze the noise caused by attacks. Because every operation is invertible, the quantization index modulation (QIM)-based method is applicable for the OFDM modulated signals. We also consider the property of watermark extracting operation in SS-based and QIM-based method and formalize their models of noisy channel in order to employ an error correcting code. The performance of their methods with error correcting code is numerically evaluated under the constraints of same distortion level in watermarked content. The experimental results indicated a criteria for the selection of SS-based and QIM-based methods for given content, which is determined by the amount of host interference. In case that the host interference is 0.8 times smaller than a watermark signal, the SS-based method is suitable. When it is 1.0 times larger, the QIM-based method should be selected.

The present paper introduces the construction of quadriphase sequences having a zero-correlation zone. For a zero-correlation zone sequence set of N sequences, each of length l, the cross-correlation function and the side lobe of the autocorrelation function of the proposed sequence set are zero for the phase shifts τ within the zero-correlation zone z, such that |τ|≤z (τ ≠ 0 for the autocorrelation function). The ratio $\frac{N(z+1)}{\ell}$ is theoretically limited to one. When l=N(z+1), the sequence set is called an optimal zero-correlation sequence set. The proposed zero-correlation zone sequence set can be generated from an arbitrary Hadamard matrix of order n. The length of the proposed sequence set can be extended by sequence interleaving, where m times interleaving can generate 4n sequences, each of length 2^m+3n. The proposed sequence set is optimal for m=0,1 and almost optimal for m>1.

Code division multiple access (CDMA) based on direct sequence (DS) spread spectrum modulation using spreading codes is one of standard technologies for multiple access communications. In asynchronous DS/CDMA communications, spreading codes with appropriate negative auto-correlation can reduce bit error rate (BER) compared with uncorrelated sequences. In this letter, we design new binary functions for generating chaotic binary sequences with negative auto-correlation using Bernoulli chaotic map. Such binary functions can be applied to the generation of spreading codes with negative auto-correlation based on existing spreading codes (e.g., shift register sequences).

Cyclic codes are a subclass of linear codes and have applications in consumer electronics, data storage systems, and communication systems as they have efficient encoding and decoding algorithms. In this letter, a class of four-weight binary cyclic codes are presented. Their weight distributions of these cyclic codes are also settled.

In this paper we study the structure of self-dual cyclic codes over the ring $\Lambda= \Z_4+u\Z_4$. The ring Λ is a local Frobenius ring but not a chain ring. We characterize self-dual cyclic codes of odd length n over Λ. The results can be used to construct some optimal binary, quaternary cyclic and self-dual codes.

In this paper, we proposed a method for radar modulation identification based on the measurement of inequality in the frequency domain. Gini's coefficient was used to exploit the inequality in the powers of spectral components. The maximum likelihood classifier was used to classify the detected radar signal into four types of modulations: unmodulated signal (UM), linear frequency modulation (LFM), non-linear frequency modulation (NLFM), and frequency shift keying (FSK). The simulation results demonstrated that the proposed method achieves an overall identification accuracy of 98.61% at a signal-to-noise ratio (SNR) of -6dB without a priori information such as carrier frequency, pulse arrival times or pulse width.

In this paper, robust stability of nonlinear feedback systems with unknown disturbance is considered by using the operator-based right coprime factorization method. For dealing with the unknown disturbance, a new design scheme and a nonlinear controller are given. That is, robust stability of the nonlinear systems with unknown disturbance is guaranteed by combining right coprime factorization with the proposed controller. Simultaneously, adverse effects resulting from the disturbance are removed by using the proposed nonlinear operator controller. Finally, a simulation example is given to show the effectiveness of the proposed design scheme of this paper.

This paper investigates open-loop Stackelberg games for a class of stochastic systems with multiple players. First, the necessary conditions for the existence of an open-loop Stackelberg strategy set are established using the stochastic maximum principle. Such conditions can be represented as solvability conditions for cross-coupled forward-backward stochastic differential equations (CFBSDEs). Second, in order to obtain the open-loop strategy set, a computational algorithm based on a four-step scheme is developed. A numerical example is then demonstrated to show the validity of the proposed method.

Particle swarm optimizer network (PSON) is one of the multi-swarm PSOs. In PSON, a population is divided into multiple sub-PSOs, each of which searches a solution space independently. Although PSON has a good solving performance, it may be trapped into a local optimum solution. In this paper, we introduce into PSON a dynamic stochastic network topology called “PSON with stochastic connection” (PSON-SC). In PSON-SC, each sub-PSO can be connected to the global best (gbest) information memory and refer to gbest stochastically. We show clearly herein that the diversity of PSON-SC is higher than that of PSON, while confirming the effectiveness of PSON-SC by many numerical simulations.

A high-image-rejection wireless receiver with an N-phase active RC complex filter is proposed and analyzed. Signal analysis shows that the double-conversion receiver with (N+N²) mixers corrects the gain and phase mismatches of the adjacent image. Monte Carlo simulations evaluate the relation between image-rejection performances and the dispersions of device parameters for the double-conversion wireless receiver. The Monte Carlo simulations show that the image rejection ratio of the adjacent image depends almost only on R and C mismatches in the complex filter.

As seen in stream data processing, it is necessary to extract a particular data field from bulk data, where we can use a field-data extractor. Particularly, an (M,N)-field-data extractor reads out any consecutive N bytes from an M-byte register by connecting its input/output using multiplexers (MUXs). However, the number of required MUXs increases too much as the input/output byte widths increase. It is known that partitioning a MUX network leads to reducing the number of MUXs. In this paper, we firstly pick up a multi-layered MUX network, which is generated by repeatedly partitioning a MUX network into a collection of single-layered MUX networks. We show that the multi-layered MUX network is equivalent to the barrel shifter from which redundant MUXs and wires are removed, and we prove that the number of required MUXs becomes the smallest among MUX-network-partitioning based field-data extractors. Next, we propose a rotator-based MUX network for a field-data extractor, which is based on reading out a particular data in an input register to a rotator. The byte width of the rotator is the same as its output register and hence we no longer require any extra wires nor MUXs. By rotating the input data appropriately, we can finally have a right-ordered data into an output register. Experimental results show that a multi-layered MUX network reduces the number of required gates to construct a field-data extractor by up to 97.0% compared with the one using a naive approach and its delay becomes 1.8ns-2.3ns. A rotator-based MUX network with a control circuit also reduces the number of required gates to construct a field-data extractor by up to 97.3% compared with the one using a naive approach and its delay becomes 2.1ns-2.9ns.

Using a matrix approach based on a Markov process, we investigate the reliability of a circular connected-(1,2)-or-(2,1)-out-of-(m,n):F lattice system for the i.i.d. case. We develop a modified linear lattice system that is equivalent to this circular system, and propose a methodology that allows the systematic calculation of the reliability. It is based on ideas presented by Fu and Hu [6]. A partial transition probability matrix is used to reduce the computational complexity of the calculations, and closed formulas are derived for special cases.

This paper studies a novel iterative detection algorithm for data detection in orthogonal frequency division multiplexing systems in the presence of phase noise (PHN) and channel estimation errors. By simplifying the maximum a posteriori algorithm based on the theory of variational inference, an optimization problem over variational free energy is formulated. After that, the estimation of data, PHN and channel state information is obtained jointly and iteratively. The simulations indicate the validity of this algorithm and show a better performance compared with the traditional schemes.

When haze exists in an image of an outdoor scene, the visibility of objects in the image is deteriorated. In recent years, to improve the visibility of objects in such images, many dehazing methods have been investigated. Most of the methods are based on the atmospheric scattering model. In such methods, the transmittance and global atmospheric light are estimated from an input image and a dehazed image is obtained by substituting them into the model. To estimate the transmittance and global atmospheric light, the dark channel prior is a major and powerful concept that is employed in many dehazing methods. In this paper, we propose a new dehazing method in which the degree of haze removal can be adjusted by changing its parameters. Our method is also based on the atmospheric scattering model and employs the dark channel prior. In our method, the estimated transmittance is adjusted to a more suitable value by a transform function. By choosing appropriate parameter values for each input image, good haze removal results can be obtained by our method. In addition, a quantitative index for evaluating the quality of a dehazed image is proposed in this paper. It can be considered that haze removal is a type of saturation enhancement. On the other hand, an output image obtained using the atmospheric scattering model is generally darker than the input image. Therefore, we evaluate the quality of dehazed images by considering the balance between the brightness and saturation of the input and output images. The validity of the proposed index is examined using our dehazing method. Then a comparison between several dehazing methods is carried out using the index. Through these experiments, the effectiveness of our dehazing method and the quantitative index is confirmed.

In this letter, a novel mainlobe anti-jamming method via eigen-projection processing and covariance matrix reconstruction is proposed. The present work mainly focuses on two aspects: the first aspect is to obtain the eigenvector of the mainlobe interference accurately in order to form the eigen-projection matrix to suppress the mainlobe interference. The second aspect is to reconstruct the covariance matrix which is uesd to calculate the adaptive weight vector for forming an ideal beam pattern. Additionally, the self-null effect caused by the signal of interest and the sidelobe interferences elimination are also considered in the proposed method. Theoretical analysis and simulation results demonstrate that the proposed method can suppress the mainlobe interference effectively and achieve a superior performance.

Compressed sensing (CS)-based wideband spectrum sensing has been a hot topic because it can cut high signal acquisition costs. However, using CS-based approaches, the spectral recovery requires large computational complexity. This letter proposes a wideband spectrum sensing algorithm based on multirate coprime sampling. It can detect the entire wideband directly from sub-Nyquist samples without spectral recovery, thus it brings a significant reduction of computational complexity. Compared with the excellent spectral recovery algorithm, i.e., orthogonal matching pursuit, our algorithm can maintain good sensing performance with computational complexity being several orders of magnitude lower.

A linear-correction method is developed for source position and velocity estimation using time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurements. The proposed technique first obtains an initial source location estimate using the first-step processing of an existing algebraic algorithm. It then refines the initial localization result by estimating via weighted least-squares (WLS) optimization and subtracting out its estimation error. The new solution is shown to be able to achieve the Cramer-Rao lower bound (CRLB) accuracy and it has better accuracy over several benchmark methods at relatively high noise levels.

Target determination based on Doppler frequency shift (DFS) measurements is a nontrivial problem because of the nonlinear relation between the position space and the measurements. The conventional methods such as numerical iterative algorithm and grid searching are used to obtain the solution, while the former requires an initial position estimate and the latter needs huge amount of calculations. In this letter, to avoid the problems appearing in those conventional methods, an effective solution is proposed, in which two best linear unbiased estimators (BULEs) are employed to obtain an explicit solution of the proximate target position. Subsequently, this obtained explicit solution is used to initialize the problem of original maximum likelihood estimation (MLE), which can provide a more accurate estimate.

A modular serial pipelined sorting architecture for continuous input sequences is presented. It supports continuous sequences, whose lengths can be dynamically changed, and does so using a very simple control strategy. It consists of identical serial cascaded sorting cells, and lends itself to high frequency implementation with any number of sorting cells, because both data and control signals are pipelined. With L cascaded sorting cells, it produces a fully sorted result for sequences whose length N is equal to or less than L+1; for longer sequences, the largest L elements are sorted out. Being modularly designed, several independent smaller sorters can be dynamically configured to form a larger sorter.

In this letter, we focus on the subcarrier allocation problem for device-to-device (D2D) communication in cellular networks to improve the cellular energy efficiency (EE). Our goal is to maximize the weighted cellular EE and its solution is obtained by using a game-theoretic learning approach. Specifically, we propose a lower bound instead of the original optimization objective on the basis of the proven property that the gap goes to zero as the number of transmitting antennas increases. Moreover, we prove that an exact potential game applies to the subcarrier allocation problem and it exists the best Nash equilibrium (NE) which is the optimal solution to optimize the lower bound. To find the best NE point, a distributed learning algorithm is proposed and then is proved that it can converge to the best NE. Finally, numerical results verify the effectiveness of the proposed scheme.

In this letter, efficient closed-form formulas for the exact and asymptotic average bit error probability (ABEP) of space shift keying (SSK) systems are derived over Rayleigh fading channels with imperfect channel state information (CSI). Specifically, for a generic 2×N_R multiple-input multiple-output (MIMO) system with the maximum likelihood (ML) detection, the impact of imperfect CSI is taken into consideration in terms of two types of channel estimation errors with the fixed variance and the variance as a function of the number of pilot symbols and signal-to-noise ratio (SNR). Then, the explicit evaluations of the bit error floor (BEF) and asymptotic SNR loss are carried out based on the derived asymptotic ABEP formula, which accounts for the impact of imperfect CSI on the SSK system. The numerical results are presented to validate the exactness of our theoretical analysis.

A chirp spread spectrum (CSS) system uses a chirp signal which changes the instantaneous frequency according to time for spreading a transmission bandwidth. In the CSS system, the transmission performance can be simply improved by increasing the time-bandwidth product which is known as the processing gain. However, increasing the transmission bandwidth is limited because of the spectrum regulation. In this letter, we propose a correlation-based chirp rate allocation method to improve the transmission performance by analyzing the cross-correlation coefficient in the same time-bandwidth product. In order to analyze the transmission performance of the proposed method, we analytically derive the cross-correlation coefficient according to the time-bandwidth separation product and simulate the transmission performance. The simulation results show that the proposed method can analytically allocate the optimal chirp rate and improve the transmission performance.

This letter proposes a Non-uniform Cell-based Index (NCI) to enable clients to quickly process window queries in the wireless spatial data broadcast environment. To improve the access time, NCI reduces the probe wait time by equalized spacing between indexes, using non-uniformly partitioned cells of data space. Through the performance evaluation, we show the proposed NCI outperforms the existing index schemes for window queries to spatial data in respect of access time.