A method of generating scenarios using differential scenaro information is presented. Behaviors of normal scenarios of similar purpose are quite similar each other, while actors and data in scenarios are different among these scenarios. We derive the differential information between them and apply the differential information to generate new alternative/exceptional scenarios. Our method will be illustrated with examples. This paper describes (1) a language for describing scenarios based on a simple case grammar of actions, (2) introduction of the differential scenario, and (3) method and examples of scenario generation using the differential scenario.

This paper presents a new common-mode stabilization method for a CMOS differential cascode Class-E power amplifier with LC-tank based driver stage. The stabilization method is based on the identification of the poles and zeros of the closed-loop transfer function at a critical node. By adding a series resistor at the common-gate node of the cascode transistor, the right-half-plane poles are moved to the left half plane, improving the common-mode stability. The simulation results show that the new method is an effective way to stabilize the PA.

The double threshold detecting strategy is widely used for spatially distributed target detection in practical systems. However, the detector is limited in terms of robustness and effectiveness. In this paper, an improved double threshold detector is proposed that avoids these shortcomings. In the proposed detector, the energy in range cells that exceed the first threshold is accumulated and then the output of the accumulator is compared with the second threshold for detection. The threshold selection strategy is derived to guarantee the constant false-alarm rate (CFAR) property. A simulation shows that the proposed detector is superior to the conventional approach in terms of both robustness and effectiveness.

Silicon Physical Unclonable Functions (PUFs) have been proposed to exploit inherent characteristics caused by process variations, such as transistor size, threshold voltage and so on, and to produce an inexpensive and tamper-resistant device such as IC identification, authentication and key generation. We have focused on the arbiter-PUF utilizing the relative delay-time difference between the equivalent paths. The conventional arbiter-PUF has a technical issue, which is low uniqueness caused by the ununiformity on response-generation. To enhance the uniqueness, a novel arbiter-based PUF utilizing the Response Generation according to the Delay Time Measurement (RG-DTM) scheme, has been proposed. In the conventional arbiter-PUF, the response 0 or 1 is assigned according to the single threshold of relative delay-time difference. On the contrary, the response 0 or 1 is assigned according to the multiple threshold of relative delay-time difference in the RG-DTM PUF. The conventional and RG-DTM PUF were designed and fabricated with 0.18 µm CMOS technology. The Hamming distances (HDs) between different chips, which indicate the uniqueness, were calculated by 256-bit responses from the identical challenges on each chip. The ideal distribution of HDs, which indicates high uniqueness, is achieved in the RG-DTM PUF using 16 thresholds of relative delay-time differences. The generative stability, which is the fluctuation of responses in the same environment, and the environmental stability, which is the changes of responses in the different environment were also evaluated. There is a trade-off between high uniqueness and high stability, however, the experimental data shows that the RG-DTM PUF has extremely smaller false matching probability in the identification compared to the conventional PUF.

In this paper, we propose a novel scheme to optimize the allocation of continuous queries in a sensor network with multiple sinks. The existing scheme compares the coverage areas of given queries and estimates the amount of sharing among them. It tries to allocate queries to the optimal sink that maximizes the amount of sharing and reduces the communication costs among sensor nodes and sinks. However, it inefficiently allocates continuous queries. The amount of sharing among continuous queries depends not only on their coverage area but also on their time-parameters like time-duration and time-interval. We define a new cost estimator with time-parameters for continuous queries and optimize their allocation in the sensor network. Simulation results show that our scheme performs the allocation of continuous queries efficiently and reduces the communication cost.

To provide scalability against group size, Global Location Search based Hierarchical Geographic Multicast Protocols (GLS-HGMPs) have recently been proposed for wireless sensor networks. To reduce the communication overhead imposed by the global location search and prevent the multicast data detour imposed by the hierarchical geographic multicasting in GLS-HGMPs, this letter proposes Local Location Search based Progressive Geographic Multicast Protocol (LLS-PGMP). Simulation results show that LLS-PGMP is superior to GLS-HGMPs.

A hybrid buffer structured optical packet switch and its scheduling algorithm are presented for a limited number of tunable wavelength convertors (TWCs) and internal wavelengths. The hybrid buffer consists of the fiber delay line (FDL) buffer and the electronic buffer. With the proposed algorithm, it could lead realizable packet loss reduction that the LAUC-VF algorithm with only the FDL buffer does not reach. Also, we optimized the number of TWCs and internal wavelengths of the hybrid buffer structured OPS. For the fully shared TWC structure, the optimum number of TWCs and internal wavelengths to guarantee minimum packet loss is evaluated to prevent resource waste under the hybrid buffer.

When a cognitive radio system dynamically utilizes a frequency band, channel control information must be communicated over the network in order for the currently available carrier frequencies to be shared. In order to keep efficient spectrum utilization, this control information should also be dynamically transmitted through channels such as cognitive pilot channels based on the channel conditions. If transmitters dynamically select carrier frequencies, receivers must receive the control signal without knowledge of its carrier frequencies. A novel scheme called differential code parallel transmission (DCPT) enables receivers to receive low-rate information without any knowledge of the carrier frequency. The transmitter simultaneously transmits two signals whose carrier frequencies are separated by a predefined value. The absolute values of the carrier frequencies can be varied. When the receiver receives the DCPT signal, it multiplies the signal by a frequency-shifted version of itself; this yields a DC component that represents the data signal, which is then demodulated. However, the multiplication process results in the noise power being squared, necessitating high received signal power. In this paper, to realize a bandpass filter that passes only DCPT signals of unknown frequency and that suppresses noise and interference at other frequencies, a DCPT-adaptive bandpass filter (ABF) that employs an adaptive equalizer is proposed. In the training phase, the received signal is the filter input and the frequency-shifted signal is the training input. Then, the filter is trained to pass the higher-frequency signal of the two DCPT signals. The performance of DCPT-ABF is evaluated through computer simulations. We find that DCPT-ABF operates successfully even under strong interference.

It is important to optimize aggregation schemes for heterogeneous wireless networks for maximizing communication throughput utilizing any available radio access networks. In the heterogeneous networks, differences of the quality of service (QoS), such as throughput, delay and packet loss rate, of the networks makes difficult to maximize the aggregation throughput. In this paper, we firstly analyze influences of such differences in QoS to the aggregation throughput, and show that it is possible to improve the throughput by adjusting the parameters of an aggregation system. Since manual parameter optimization is difficult and takes much time, we propose an autonomous parameter tuning scheme using a machine learning algorithm for the heterogeneous wireless network aggregation. We implement the proposed scheme on a heterogeneous cognitive radio network system. The results on our experimental network with network emulators show that the proposed scheme can improve the aggregation throughput better than the conventional schemes. We also evaluate the performance using public wireless network services, such as HSDPA, WiMAX and W-CDMA, and verify that the proposed scheme can improve the aggregation throughput by iterating the learning cycle even for the public wireless networks. Our experimental results show that the proposed scheme achieves twice better aggregation throughput than the conventional schemes.

This paper proposes an all-digital process variability monitor based on a shared structure of a buffer ring and a ring oscillator. The proposed circuit monitors the PMOS and NMOS process variabilities independently according to a count number of a single pulse which propagates on the ring during the buffer ring mode, and an oscillation period during the ring oscillator mode. Using this shared-ring structure, we reduce the occupation area about 40% without loss of process variability monitoring properties compared with the conventional circuit. The proposed shared-ring circuit has been fabricated in 65 nm CMOS process and the measurement results with two different wafer lots show the feasibility of the proposed process variability monitoring scheme.

The frequency regions and spectral features that can be used to measure the perceived similarity and continuity of voice quality are reported here. A perceptual evaluation test was conducted to assess the naturalness of spoken sentences in which either a vowel or a long vowel of the original speaker was replaced by that of another. Correlation analysis between the evaluation score and the spectral feature distance was conducted to select the spectral features that were expected to be effective in measuring the voice quality and to identify the appropriate speech segment of another speaker. The mel-frequency cepstrum coefficient (MFCC) and the spectral center of gravity (COG) in the low-, middle-, and high-frequency regions were selected. A perceptual paired comparison test was carried out to confirm the effectiveness of the spectral features. The results showed that the MFCC was effective for spectra across a wide range of frequency regions, the COG was effective in the low- and high-frequency regions, and the effective spectral features differed among the original speakers.

Reliable detection of the licensed user signal is a pre-requirement for avoiding interference to the licensed user in a CR network. Cooperative spectrum sensing (CSS) is able to offer improved sensing performance compared to individual sensing. In this paper, we propose a robust soft combination rule based on the Kullback-Leibler divergence (KL-divergence) for CSS. The proposed scheme is able to obtain a similar sensing performance compared to that of maximum gain combination (MGC) without requiring signal to noise ratio (SNR) information. In addition, the proposed scheme protects the sensing process against common types of malicious users without a malicious user identification step. The simulation results demonstrate the effectiveness of the proposed scheme.

In this paper, a high-throughput debloking filter is presented for H.264/AVC standard, catering video applications with 4 K2 K (40962304) ultra-definition resolution. In order to strengthen the parallelism without simply increasing the area, we propose a luma-chroma parallel method. Meanwhile, this work reduces the number of processing cycles, the amount of external memory traffic and the working frequency, by using triple four-stage pipeline filters and a luma-chroma interlaced sequence. Furthermore, it eliminates most unnecessary off-chip memory bandwidth with a highly reusable memory scheme, and adopts a “slide window” buffer scheme. As a result, our design can support 4 K2 K at 30 fps applications at the working frequency of only 70.8 MHz.

of late, many researchers have been interested in sparse representation of signals and its applications such as Compressive Sensing in Cognitive Radio (CR) networks as a way of overcoming the issue of limited bandwidth. Compressive sensing based wideband spectrum sensing is a novel approach in cognitive radio systems. Also in these systems, using spatial-frequency opportunistic reuse is emerged interestingly by constructing and deploying spatial-frequency Power Spectral Density (PSD) maps. Since the CR sensors are distributed in the region of support, the sensed PSD by each sensor should be transmitted to a master node (base-station) in order to construct the PSD maps in space and frequency domains. When the number of sensors is large, this data transmission which is required for construction of PSD map can be challenging. In this paper, in order to transmit the CR sensors' data to the master node, the compressive sensing based scheme is used. Therefore, the measurements are sampled in a lower sampling rate than of the Nyquist rate. By using the proposed method, an acceptable PSD map for cognitive radio purposes can be achieved by only 30% of full data transmission. Also, simulation results show the robustness of the proposed method against the channel variations in comparison with classical methods. Different solution schemes such as Basis Pursuit, Lasso, Lars and Orthogonal Matching Pursuit are used and the quality performance of them is evaluated by several simulation results over a Rician channel with respect to several different compression and Signal to Noise Ratios. It is also illustrated that the performance of Basis Pursuit and Lasso methods outperform the other compression methods particularly in higher compression rates.

We propose a distributed node selection (DNS) scheme that guarantees quality of service (QoS) of the scalable video broadcasting system over wireless channels. The proposed DNS scheme chooses the destination node based on the SVC layer information, and it selects the best relay from a set of competing candidate nodes by considering two factors: 1) wireless channel conditions between destination and relay candidates and 2) scalable video's layer information. In simulations, the performance of the proposed scheme in terms of quality gains, complexity (overhead) and applicability was examined.

Mobility Robustness Optimization (MRO) is one of the most important goals in LTE-Advanced Self-Organizing Networks (SON). Seamless handover in femtocell network is urgent and challenging, which has not been paid enough attention. Handover decision parameters, such as Time-To-Trigger (TTT), Hysteresis, Cell Individual Offset (CIO), have great effect on mobility performance, which may lead to Radio Link Failures (RLFs) and Unnecessary Handover. This letter proposes a handover parameters optimization approach based on Ant Colony Algorithm in the femtocell networks. The simulation result shows that the proposed scheme has a better performance than the fixed parameters method.

Keith Salvin presented a key exchange protocol using matrices in the general linear group, GL(r,Zn), where n is the product of two distinct large primes. The system is fully specified in the US patent number 7346162 issued in 2008. In the patent claims, it is argued that the best way to break this system is to factor n. Furthermore, for efficiency reasons, it is suggested to use r=2. In this letter, we show that this cryptosystem can be easily broken by solving a set of consistent homogeneous r2 linear equations in 2r unknowns over Zn.

Zero-knowledge arguments allows one party to prove that a statement is true, without leaking any other information than the truth of the statement. In many applications such as verifiable shuffle (as a practical application) and circuit satisfiability (as a theoretical application), zero-knowledge arguments for mathematical statements related to linear algebra are essentially used. Groth proposed (at CRYPTO 2009) an elegant methodology for zero-knowledge arguments for linear algebraic relations over finite fields. He obtained zero-knowledge arguments of the sub-linear size for linear algebra using reductions from linear algebraic relations to equations of the form z=x*'y, where x, y ∈ Fnp are committed vectors, z ∈ Fp is a committed element, and *': FnpFnpFp is a bilinear map. These reductions impose additional rounds on zero-knowledge arguments of the sub-linear size. The round complexity of interactive zero-knowledge arguments is an important measure along with communication and computational complexities. We focus on minimizing the round complexity of sub-linear zero-knowledge arguments for linear algebra. To reduce round complexity, we propose a general transformation from a t-round zero-knowledge argument, satisfying mild conditions, to a (t-2)-round zero-knowledge argument; this transformation is of independent interest.

This paper proposes a direction-of-arrival (DOA) estimation method of multiple speech sources from a stereophonic mixture in an underdetermined case where the number of sources exceeds the number of sensors. The method relies on the sparseness of speech signals in time-frequency (T-F) domain representation which means multiple independent speakers have a small overlap. At first, a selection of T-F cells bearing reliable spatial information is proposed by an introduced reliability index which is defined by the estimated interaural phase difference at each T-F cell. Then, a statistical error propagation model between the phase difference at T-F cell and its consequent DOA is introduced. By employing this model and the sparseness in T-F domain the DOA estimation problem is altered to obtaining local peaks of probability density function of DOA. Finally the kernel density estimator approach based on the proposed statistical model is applied. The performance of the proposed method is assessed by conducted experiments. Our method outperforms others both in accuracy for real observed data and in robustness for simulation with additional diffused noise.

This study investigates the effect of frame intervals on the accuracy of the Lucas–Kanade optical flow estimates for high-frame-rate (HFR) videos, with a view to realizing accurate HFR-video-based optical flow estimation. For 512 512 pixels videos of patterned objects moving at different speeds and captured at 1000 frames per second, the averages and standard deviations of the estimated optical flows were determined as accuracy measures for frame intervals of 1–40 ms. The results showed that the accuracy was highest when the displacement between frames was around 0.6 pixel/frame. This common property indicates that accurate optical flow estimation for HFR videos can be realized by varying frame intervals according to the motion field: a small frame interval for high-speed objects and a large frame interval for low-speed objects.