The key escrow problem and high computational cost are the two major problems that hinder the wider adoption of hierarchical identity-based signature (HIBS) scheme. HIBS schemes with either escrow-free (EF) or online/offline (OO) model have been proved secure in our previous work. However, there is no much EF or OO scheme that has been evaluated experimentally. In this letter, several EF/OO HIBS schemes are considered. We study the algorithmic complexity of the schemes both theoretically and experimentally. Scheme performance and practicability of EF and OO models are discussed.

Patarin proposed a crytographic trapdoor called Hidden Field Equation (HFE), a trapdoor based on the Multivariate Quadratic (MQ) and the Isomorphism of Polynomials (IP) problems. The MQ problem was proved by Patarin et al.'s to be NP-complete. Although the basic HFE has been proved to be vulnerable to attacks, its variants obtained by some modifications have been proved to be stronger against attacks. The Quartz digital signature scheme based on the HFEv- trapdoor (a variant of HFE) with particular choices of parameters, has been shown to be stronger against algebraic attacks to recover the private key. Furthermore, it generates reasonably short signatures. However, Joux et al. proved (based on the Birthday Paradox Attack) that Quartz is malleable in the sense that, if an adversary gets a valid pair of message and signature, a valid signature to another related message is obtainable with 250 computations and 250 queries to the signing oracle. Currently, the recommended minimum security level is 2112. Our signature scheme is also based on Quartz but we achieve a 2112 security level against Joux et al.'s attack. It is also more efficient in signature verification and vector initializations. Furthermore, we implemented both the original and our improved Quartz signature and run empirical comparisons.

Faster-than-Nyquist (FTN) signaling is investigated for quasi-static flat fading massive multiple-input multiple-output (MIMO) systems. In FTN signaling, pulse trains are sent at a symbol rate higher than the Nyquist rate to increase the transmission rate. As a result, inter-symbol interference occurs inevitably for flat fading channels. This paper assesses the information-theoretically achievable rate of MIMO FTN signaling based on the optimum joint equalization and multiuser detection. The replica method developed in statistical physics is used to evaluate the achievable rate in the large-system limit, where the dimensions of input and output signals tend to infinity at the same rate. An analytical expression of the achievable rate is derived for general modulation schemes in the large-system limit. It is shown that FTN signaling does not improve the channel capacity of massive MIMO systems, and that FTN signaling with quadrature phase-shift keying achieves the channel capacity for all signal-to-noise ratios as the symbol period tends to zero.

The previous researches on the chaotic CDMA have theoretically derived the chaotic sequences having the minimum asynchronous cross-correlation. To minimize the asynchronous cross-correlation, autocorrelation of each sequence have to be C(τ)≈C×rτ, r=-2+√3, dumped oscillation with increase of the lag τ. There are several methods to generate such sequences, using a chaotic map, using the Lebesgue spectrum filter (LSF) and so on. In this paper, such lowest cross-correlation found in the chaotic CDMA researches is applied to solution search algorithms for combinatorial optimization problems. In combinatorial optimization, effectiveness of the chaotic search has already been clarified. First, an importance of chaos and autocorrelation with dumped oscillation for combinatorial optimization is shown. Next, in order to realize ideal solution search, the LSF is applied to the Hopfield-Tank neural network, the 2-opt method and the 2-exchange method. Effectiveness of the LSF is clarified even for the large problems for the traveling salesman problems and the quadratic assignment problems.

Spatial stochastic models have been much used for performance analysis of wireless communication networks. This is due to the fact that the performance of wireless networks depends on the spatial configuration of wireless nodes and the irregularity of node locations in a real wireless network can be captured by a spatial point process. Most works on such spatial stochastic models of wireless networks have adopted homogeneous Poisson point processes as the models of wireless node locations. While this adoption makes the models analytically tractable, it assumes that the wireless nodes are located independently of each other and their spatial correlation is ignored. Recently, the authors have proposed to adopt the Ginibre point process — one of the determinantal point processes — as the deployment models of base stations (BSs) in cellular networks. The determinantal point processes constitute a class of repulsive point processes and have been attracting attention due to their mathematically interesting properties and efficient simulation methods. In this tutorial, we provide a brief guide to the Ginibre point process and its variant, α-Ginibre point process, as the models of BS deployments in cellular networks and show some existing results on the performance analysis of cellular network models with α-Ginibre deployed BSs. The authors hope the readers to use such point processes as a tool for analyzing various problems arising in future cellular networks.

In this paper, a built-in test circuit for an electrical interconnect test method is proposed to detect an open defect occurring at an interconnect between an IC and a printed circuit board. The test method is based on measuring the supply current of an inverter gate in the test circuit. A time-varying signal is provided to an interconnect as a test signal by the built-in test circuit. In this paper, the test circuit is evaluated by SPICE simulation and by experiments with a prototyping IC. The experimental results reveal that a hard open defect is detectable by the test method in addition to a resistive open defect and a capacitive open one at a test speed of 400 kHz.

A method of color scheme is proposed considering contrast of luminance between adjacent regions and design property. This method aims at setting the contrast of luminance high, in order to make the image understandable to visually handicapped people. This method also realizes preferable color design for visually normal people by assigning color components from color combination samples. Interactive evolutionary computing is adopted to design the luminance and the color, so that the luminance and color components are assigned to each region appropriately on the basis of human subjective criteria. Here, the luminance is designed first, and then color components are assigned, keeping the luminance unchanged. Since samples of fine color combinations are applied, the obtained color design is also fine and harmonic. Computer simulations verify the high performance of this system.

We propose a novel method for estimating acoustic scenes such as user activities, e.g., “cooking,” “vacuuming,” “watching TV,” or situations, e.g., “being on the bus,” “being in a park,” “meeting,” utilizing the information of acoustic events. There are some methods for estimating acoustic scenes that associate a combination of acoustic events with an acoustic scene. However, the existing methods cannot adequately express acoustic scenes, e.g., “cooking,” that have more than one subordinate category, e.g., “frying ingredients” or “plating food,” because they directly associate acoustic events with acoustic scenes. In this paper, we propose an acoustic scene estimation method based on a hierarchical probabilistic generative model of an acoustic event sequence taking into account the relation among acoustic scenes, their subordinate categories, and acoustic event sequences. In the proposed model, each acoustic scene is represented as a probability distribution over their unsupervised subordinate categories, called “acoustic sub-topics,” and each acoustic sub-topic is represented as a probability distribution over acoustic events. Acoustic scene estimation experiments with real-life sounds showed that the proposed method could correctly extract subordinate categories of acoustic scenes.

This paper presents a weighted diversity combining technique for the cyclostationarity detection based spectrum sensing of orthogonal frequency division multiplexing signals in cognitive radio. In cognitive radio systems, secondary users must detect the desired signal in an extremely low signal-to-noise ratio (SNR) environment. In such an environment, multiple antenna techniques (space diversity) such as maximum ratio combining are not effective because the energy of the target signal is also extremely weak, and it is difficult to synchronize some received signals. The cyclic autocorrelation function (CAF) is used for traditional cyclostationarity detection based spectrum sensing. In the presented technique, the CAFs of the received signals are combined, while the received signals themselves are combined with general space diversity techniques. In this paper, the value of the CAF at peak and non-peak cyclic frequencies are computed, and we attempt to improve the sensing performance by using different weights for each CAF value. The results were compared with those from conventional methods and showed that the presented technique can improve the spectrum sensing performance.

We consider the problem of sparse signal recovery from 1-bit measurements. Due to the noise present in the acquisition and transmission process, some quantized bits may be flipped to their opposite states. These sign flips may result in severe performance degradation. In this study, a novel algorithm, termed HISTORY, is proposed. It consists of Hamming support detection and coefficients recovery. The HISTORY algorithm has high recovery accuracy and is robust to strong measurement noise. Numerical results are provided to demonstrate the effectiveness and superiority of the proposed algorithm.

Recently, Doppler radars have been used in various applications from the detection and the classification of indoor human activities to the detection of airplanes. To improve both the degrees of freedom (DOF) and the estimation accuracy of the direction-of-arrival (DOA) of targets, multiple-input multiple-output (MIMO) radar has received much attention in recent years. The temporal spatial virtual array based on Doppler shift of a moving target has been one of methods to improve DOA estimation accuracy. However, the DOA estimation accuracy based on the method depends on the velocity and the direction of the target on which we focus. Also, the temporal spatial virtual array should be generated based on the information of the single target. Thus, it is difficult to implement the method if there are multiple targets. In this paper, we propose a new method that provides high accuracy of DOA estimation by using the temporal spatial virtual array without dependence on the velocity, the direction and the number of existing targets. We demonstrate the DOA estimation accuracy and the effectiveness of the proposed method via simulations.

The scan segmentation method is an efficient solution to deal with the test power problem; However, the use of multiple capture cycles may cause capture violations, thereby leading to fault coverage loss. This issue is much more severe in at-speed testing. In this paper, two scan partition schemes based on complex networks clustering ara proposed to minimize the capture violations without increasing test-data volume and extra area overhead. In the partition process, we use a more accurate notion, spoiled nodes, instead of violation edges to analyse the dependency of flip-flops (ffs), and we use the shortest-path betweenness (SPB) method and the Laplacian-based graph partition method to find the best combination of these flip-flops. Beyond that, the proposed methods can use any given power-unaware set of patterns to test circuits, reducing both shift and capture power in at-speed testing. Extensive experiments have been performed on reference circuit ISCAS89 and IWLS2005 to verify the effectiveness of the proposed methods.

We propose an edge-preserving multiscale image decomposition method using filters for non-equispaced signals. It is inspired by the domain transform, which is a high-speed edge-preserving smoothing method, and it can be used in many image processing applications. One of the disadvantages of the domain transform is sensitivity to noise. Even though the proposed method is based on non-equispaced filters similar to the domain transform, it is robust to noise since it employs a multiscale decomposition. It uses the Laplacian pyramid scheme to decompose an input signal into the piecewise-smooth components and detail components. We design the filters by using an optimization based on edge-preserving smoothing with a conversion of signal distances and filters taking into account the distances between signal intervals. In addition, we also propose construction methods of filters for non-equispaced signals by using arbitrary continuous filters or graph spectral filters in order that various filters can be accommodated by the proposed method. As expected, we find that, similar to state-of-the-art edge-preserving smoothing techniques, including the domain transform, our approach can be used in many applications. We evaluated its effectiveness in edge-preserving smoothing of noise-free and noisy images, detail enhancement, pencil drawing, and stylization.

In the European satellite broadcasting specifications, the symbol rate and the carrier frequency are not regulated. Furthermore, the first generation format DVB-S does not have any control signals. In a practical environment, the received signal condition is not stable due to the imperfect reception environment, i.e., unterminated receiver ports, cheap indoor wiring cables etc. These issues prevent correct detection of the satellite signals. For this reason, the conventional signal detection method uses brute force search for detecting the received signal's cyclostationarity, which is an extremely time-consuming approach. A coarse estimation method of the carrier frequency and the bandwidth was proposed by us based on the power spectrum. We extend this method to create a new method for detecting satellite broadcasting signals, which can significantly reduce the search range. In other words, the proposed method can detect the signals in a relatively short time. In this paper, the proposed method is applied to signals received in an actual environment. Our analysis shows that the proposed method can effectively reduce the detection time at almost a same detection performance.

We reported a secure scan design approach using shift register equivalents (SR-equivalents, for short) that are functionally equivalent but not structurally equivalent to shift registers [10 and also introduced generalized shift registers (GSRs, for short) to apply them to secure scan design [11]-[13]. In this paper, we combine both concepts of SR-equivalents and GSRs and consider the synthesis problem of SR-equivalent GSRs, i.e., how to modify a given GSR to an SR-equivalent GSR. We also consider the enumeration problem of SR-equivalent GFSRs, i.e., the cardinality of the class of SR-equivalent GSRs to clarify the security level of the secure scan architecture.

In this paper, we propose an overloaded multiple-input multiple-output (MIMO) signal detection scheme with slab decoding and lattice reduction (LR). The proposed scheme firstly splits the transmitted signal vector into two parts, the post-voting vector composed of the same number of signal elements as that of receive antennas, and the pre-voting vector composed of the remaining elements. Secondly, it reduces the candidates of the pre-voting vector using slab decoding and determines the post-voting vectors for each pre-voting vector candidate by LR-aided minimum mean square error (MMSE)-successive interference cancellation (SIC) detection. From the performance analysis of the proposed scheme, we derive an upper bound of the error probability and show that it can achieve the full diversity order. Simulation results show that the proposed scheme can achieve almost the same performance as the optimal ML detection while reducing the required computational complexity.

We study the correlation matrix element properties in array signal processing and apply them to a Direction-Of-Arrival (DOA) estimation problem of coherent or highly-correlated sources for a Uniform Linear Array (ULA). The proposed algorithm is generally based on the relation between the elements of the array correlation matrix and does not need an eigendecomposition, iteration, or angular peak-search. The performance of the proposed method was evaluated through a computer simulation.

This paper describes a blind frequency offset estimator (FOE) with wide frequency range for coherent quadrature amplitude modulation (QAM) receivers. The FOE combines a spectrum-based frequency offset estimation algorithm as a coarse estimator with a frequency offset estimation algorithm using the periodogram as a fine estimator. To establish our design methodology, each block of the FOE is rigorously analyzed by using formulas and the minimum fast Fourier transform (FFT) size that generates a frequency spectrum for both the coarse and fine estimators is determined. The coarse estimator's main feature is that all estimation processes are carried out in the frequency domain, which yields convergence more than five times faster than that of conventional estimators. The estimation frequency range of the entire FOE is more than 1.8 times wider than that of conventional FOEs. Experiments on coherent optical 64-ary QAM (64-QAM) reveal that frequency offset estimation can be achieved under a frequency offset value greater than the highest value of the conventional estimation range.

Recently, multi-user multiple-input multiple-output (MU-MIMO) systems are being widely studied. For interference cancellation, MU-MIMO commonly uses spatial precoding techniques. These techniques, however, require the transmitters to have perfect knowledge of the downlink channel state information (CSI), which is hard to achieve in high mobility environments. Instead of spatial precoding, a collaborative interference cancellation (CIC) technique can be implemented for these environments. In CIC, mobile stations (MSs) collaborate and share their received signals to increase the demultiplexing capabilities. To obtain efficient signal-exchange between collaborating users, signal selection can be implemented. In this paper, a signal selection scheme suitable for a QRM-MLD algorithm is proposed. The proposed scheme uses the minimum Euclidean distance criterion to obtain an optimum bit error rate (BER) performance. Numerical results obtained through computer simulations show that the proposed scheme is able to provide BER performance near to that of MLD even when the number of candidates in QRM-MLD is relatively small. In addition, the proposed scheme is feasible to implement owing to its low computational complexity.

This paper presents a new approach for circuit matching using signatures. We have defined a signature based on topology of the fanin cones of the circuit elements. Given two circuits, first we find all the circuit elements with unique signature between the two input circuits. After that, we try to expand the matching area by our expansion rules as much as possible. We iteratively find the unique matches and expand the matching area until no further matching is possible. Our experiments on IWLS2005 benchmark suite show that our method is able to find the perfect matching between two 160,000-gate IP in 5 minutes. In addition, our method is more than one order of magnitude faster than our previous signature-based matching method, while the size of the matched area is comparable or larger.