This paper studies the performance of the quantitative RF power variation in Radio-over-Fiber beam forming system utilizing a phased array-antenna integrating photo-diodes in downlink network for next generation millimeter wave band radio access. Firstly, we described details of fabrication of an integrated photonic array-antenna (IPA), where a 60GHz patch antenna 4×2 array and high-speed photo-diodes were integrated into a substrate. We evaluated RF transmission efficiency as an IPA system for Radio-over-Fiber (RoF)-based mobile front hall architecture with remote antenna beam forming capability. We clarified the characteristics of discrete and integrated devices such as an intensity modulator (IM), an optical fiber and the IPA and calculated RF power radiated from the IPA taking account of the measured data of the devices. Based on the experimental results on RF tone signal transmission by utilizing the IPA, attainable transmission distance of wireless communication by improvement and optimization of the used devices was discussed. We deduced that the antenna could output sufficient power when we consider that the cell size of the future mobile communication systems would be around 100 meters or smaller.

In this paper, we consider the partial gathering problem of mobile agents in arbitrary networks. The partial gathering problem is a generalization of the (well-investigated) total gathering problem, which requires that all the agents meet at the same node. The partial gathering problem requires, for a given positive integer g, that each agent should move to a node and terminate so that at least g agents should meet at each of the nodes they terminate at. The requirement for the partial gathering problem is no stronger than that for the total gathering problem, and thus, we clarify the difference on the move complexity between them. First, we show that agents require Ω(gn+m) total moves to solve the partial gathering problem, where n is the number of nodes and m is the number of communication links. Next, we propose a deterministic algorithm to solve the partial gathering problem in O(gn+m) total moves, which is asymptotically optimal in terms of total moves. Note that, it is known that agents require Ω(kn+m) total moves to solve the total gathering problem in arbitrary networks, where k is the number of agents. Thus, our result shows that the partial gathering problem is solvable with strictly fewer total moves compared to the total gathering problem in arbitrary networks.

Since camera networks for surveillance are becoming extremely dense, finding the most informative and desirable views from different cameras are of increasing importance. In this paper, we propose a camera selection method to achieve the goal of providing the clearest visibility possible and selecting the cameras which exactly capture targets for the far-field surveillance. We design a benefit function that takes into account image visibility and the degree of target matching between different cameras. Here, visibility is defined using the entropy of intensity histogram distribution, and the target correspondence is based on activity features rather than photometric features. The proposed solution is tested in both artificial and real environments. A performance evaluation shows that our target correspondence method well suits far-field surveillance, and our proposed selection method is more effective at identifying the cameras that exactly capture the surveillance target than existing methods.

In this letter, as a generalization of Heng's constructions in the paper [9], a construction of codebooks, which meets the Welch bound asymptotically, is proposed. The parameters of codebooks presented in this paper are new in some cases.

As IT systems, including network systems using SDN/NFV technologies, become large-scaled and complicated, the cost of system management also increases rapidly. Network operators have to maintain their workflow in constructing and consistently updating such complex systems, and thus these management tasks in generating system update plan are desired to be automated. Declarative system update with state space search is a promising approach to enable this automation, however, the current methods is not enough scalable to practical systems. In this paper, we propose a novel heuristic approach to greatly reduce computation time to solve system update procedure for practical systems. Our heuristics accounts for structural bottleneck of the system update and advance search to resolve bottlenecks of current system states. This paper includes the following contributions: (1) formal definition of a novel heuristic function specialized to system update for A* search algorithm, (2) proofs that our heuristic function is consistent, i.e., A* algorithm with our heuristics returns a correct optimal solution and can omit repeatedly expansion of nodes in search spaces, and (3) results of performance evaluation of our heuristics. We evaluate the proposed algorithm in two cases; upgrading running hypervisor and rolling update of running VMs. The results show that computation time to solve system update plan for a system with 100 VMs does not exceed several minutes, whereas the conventional algorithm is only applicable for a very small system.

We investigate enumeration of distinct flat-foldable crease patterns under the following assumptions: positive integer n is given; every pattern is composed of n lines incident to the center of a sheet of paper; every angle between adjacent lines is equal to 2π/n; every line is assigned one of “mountain,” “valley,” and “flat (or consequently unfolded)”; crease patterns are considered to be equivalent if they are equal up to rotation and reflection. In this natural problem, we can use two well-known theorems for flat-foldability: the Kawasaki Theorem and the Maekawa Theorem in computational origami. Unfortunately, however, they are not enough to characterize all flat-foldable crease patterns. Therefore, so far, we have to enumerate and check flat-foldability one by one using computer. In this study, we develop the first algorithm for the above stated problem by combining these results in a nontrivial way and show its analysis of efficiency.

Many users are exposed to threats of drive-by download attacks through the Web. Attackers compromise vulnerable websites discovered by search engines and redirect clients to malicious websites created with exploit kits. Security researchers and vendors have tried to prevent the attacks by detecting malicious data, i.e., malicious URLs, web content, and redirections. However, attackers conceal parts of malicious data with evasion techniques to circumvent detection systems. In this paper, we propose a system for detecting malicious websites without collecting all malicious data. Even if we cannot observe parts of malicious data, we can always observe compromised websites. Since vulnerable websites are discovered by search engines, compromised websites have similar traits. Therefore, we built a classifier by leveraging not only malicious but also compromised websites. More precisely, we convert all websites observed at the time of access into a redirection graph and classify it by integrating similarities between its subgraphs and redirection subgraphs shared across malicious, benign, and compromised websites. As a result of evaluating our system with crawling data of 455,860 websites, we found that the system achieved a 91.7% true positive rate for malicious websites containing exploit URLs at a low false positive rate of 0.1%. Moreover, it detected 143 more evasive malicious websites than the conventional content-based system.

Two-dimensional (2-D) maximally flat finite impulse response (FIR) digital filters have flat characteristics in both passband and stopband. 2-D maximally flat diamond-shaped half-band FIR digital filter can be designed very efficiently as a special case of 2-D half-band FIR filters. In some cases, this filter would require the reduction of the filter lengths for one of the axes while keeping the other axis unchanged. However, the conventional methods can realize such filters only if difference between each order is 2, 4 and 6. In this paper, we propose a closed-form frequency response of 2-D low-pass maximally flat diamond-shaped half-band FIR digital filters with arbitrary filter orders. The constraints to treat arbitrary filter orders are firstly proposed. Then, a closed-form transfer function is achieved by using Bernstein polynomial.

A diversity strategy is efficient to reduce the fluctuation of communication quality caused by fading. In order to further maintain the communication quality and improve the communication capacity, this paper proposes a two-dimensional diversity approach by serially-concatenating spectral precoding and power normalized-differential space time block coding (PN-DSTBC). Spectral precoding is able to take benefit from a frequency diversity effect without loss in spectral efficiency. In addition, PN-DSTBC is robust against serious phase noise in an extremely high frequency (EHF) band by exploiting a spatial diversity effect. However, there is a problem that a naive concatenation degrades the performance due to the imbalance of equivalent noise variances over transmit frequencies. Thus, we examine an equalized PN-DSTBC decoder as a modified approach to uniform equivalent noise variances over frequencies. The performance evaluation using computer simulations shows that the proposed modified approach yields the performance improvement at any modulation schemes and at any number of transmit frequencies. Furthermore, in the case of 64QAM and two transmit frequencies, the performance gain of the modified approach is 4dB larger than that of PN-DSTBC only at uncoded BER=10-4.

We formulate the design of an optimal quantizer as an optimization problem that finds the quantization indices that minimize quantization error. As a solution of the optimization problem, an approach based on dynamic programming, which is called DP quantization, is proposed. It is observed that quantized signals do not always contain all kinds of signal values which can be represented with given bit-depth. This property is called amplitude sparseness. Because quantization is the amplitude discretization of signal value, amplitude sparseness is closely related to quantizer design. Signal values with zero frequency do not impact quantization error, so there is the potential to reduce the complexity of the optimal quantizer by not computing signal values that have zero frequency. However, conventional methods for DP quantization were not designed to consider amplitude sparseness, and so fail to reduce complexity. The proposed algorithm offers a reduced complexity optimal quantizer that minimizes quantization error while addressing amplitude sparseness. Experimental results show that the proposed algorithm can achieve complexity reduction over conventional DP quantization by 82.9 to 84.2% on average.

A class of multimodulus algorithms (MMA(p)) optimized by an optimal step-size (OS) for blind equalization are firstly investigated in this letter. The multimodulus (MM) criterion is essentially a split cost function that separately implements the real and imaginary part of the signal, hence the phase can be recovered jointly with equalization. More importantly, the step-size leading to the minimum of the MM criterion along the search direction can be obtained algebraically among the roots of a higher-order polynomial at each iteration, thus a robust optimal step-size multimodulus algorithm (OS-MMA(p)) is developed. Experimental results demonstrate improved performance of the proposed algorithm in mitigating the inter-symbol interference (ISI) compared with the OS constant modulus algorithm (OS-CMA). Besides, the computational complexity can be reduced by the proposed OS-MMA(2) algorithm.

This paper deals with the minimum and maximum value distributions based on the n-variate FGM copula with one dependence parameter. The ranges of dependence parameters are theoretically determined so that the probability density function always takes a non-negative value. However, the closed-form conditions of the ranges for the dependence parameters have not been known in the literature. In this paper, we newly provide the necessary conditions of the ranges of the dependence parameters for the minimum and maximum value distributions which are derived from FGM copula, and show the asymptotic properties of the ranges.

One of essential requirements for the next generation communications is to support higher spectral efficiency (SE) and energy efficiency (EE) than the existing communication system. For increasing the SE, carrier aggregation (CA) has received great attention. In this paper, we propose an energy efficient smart crest factor reduction (E2S-CFR) method for increasing the EE while satisfying the required SE when the CA is applied. The proposed E2S-CFR exploits different weights on each carrier according to the required error vector magnitude (EVM), and efficiently reduces the peak to average power ratio (PAR). Consequently, we can reduce the bias voltage of a power amplifier, and it leads to save total consumed energy. Through performance evaluation, we demonstrate that the proposed E2S-CFR improves the EE by 11.76% compared to the existing schemes.

As an emerging and promising technique, device-free localization (DFL) has drawn considerable attention in recent years. By exploiting the inherent spatial sparsity of target localization, the compressive sensing (CS) theory has been applied in DFL to reduce the number of measurements. In practical scenarios, a prior knowledge about target locations is usually available, which can be obtained by coarse localization or tracking techniques. Among existing CS-based DFL approaches, however, few works consider the utilization of prior knowledge. To make use of the prior knowledge that is partly or erroneous, this paper proposes a novel faulty prior knowledge aided multi-target device-free localization (FPK-DFL) method. It first incorporates the faulty prior knowledge into a three-layer hierarchical prior model. Then, it estimates location vector and learns model parameters under a variational Bayesian inference (VBI) framework. Simulation results show that the proposed method can improve the localization accuracy by taking advantage of the faulty prior knowledge.

This letter proposes a comprehensive assessment of the mission-level damage caused by cyberattacks on an entire defense mission system. We experimentally prove that our method produces swift and accurate assessment results and that it can be applied to actual defense applications. This study contributes to the enhancement of cyber damage assessment with a faster and more accurate method.

A novel time-series relationship among four consecutive real-valued single-tone sinusoid samples is proposed based on their linear prediction property. In order to achieve unbiased frequency estimates for a real sinusoid in white noise, based on the proposed four-point time-series relationship, a constrained least squares cost function is minimized based on the unit-norm principle. Closed-form expressions for the variance and the asymptotic expression for the variance of the proposed frequency estimator are derived, facilitating a theoretical performance comparison with the existing three-point counterpart, called as the reformed Pisarenko harmonic decomposer (RPHD). The region of performance advantage of the proposed four-point based constrained least squares frequency estimator over the RPHD is also discussed. Computer simulations are conducted to support our theoretical development and to compare the proposed estimator performance with the RPHD as well as the Cramer-Rao lower bound (CRLB).

To optimize the performance of FIR filters that have low computation complexity, this paper proposes a hybrid design consisting of two optimization levels. The first optimization level is based on cyclic-shift synthesis, in which all possible sub filters (or windowed sub filters) with distinct cycle shifts are averaged to generate a synthesized filter. Due to the fact that the ripples of these sub filters' transfer curves can be individually compensated, this synthesized filter attains improved performance (besides two uprushes occur on the edges of a transition band) and thus this synthesis actually plays the role of ‘natural optimization’. Furthermore, this synthesis process can be equivalently summarized into a 3-step closed-form procedure, which converts the multi-variable optimization into a single-variable optimization. Hence, to suppress the uprushes, what the second optimization level (by Differential Evolution (DE) algorithm) needs to do is no more than searching for the optimum transition point which incurs only minimal complexity . Owning to the combination between the cyclic-shift synthesis and DE algorithm, unlike the regular evolutionary computing schemes, our hybrid design is more attractive due to its narrowed search space and higher convergence speed . Numerical results also show that the proposed design is superior to the conventional DE design in both filter performance and design efficiency, and it is comparable to the Remez design.

In parallel computing systems, the interconnection network forms the critical infrastructure which enables robust and scalable communication between hundreds of thousands of nodes. The traditional packet-switched network tends to suffer from long communication time when network congestion occurs. In this context, we explore the use of circuit switching (CS) to replace packet switches with custom hardware that supports circuit-based switching efficiently with low latency. In our target CS network, a certain amount of bandwidth is guaranteed for each communication pair so that the network latency can be predictable when a limited number of node pairs exchange messages. The number of allocated time slots in every switch is a direct factor to affect the end-to-end latency, we thereby improve the slot utilization and develop a network topology generator to minimize the number of time slots optimized to target applications whose communication patterns are predictable. By a quantitative discrete-event simulation, we illustrate that the minimum necessary number of slots can be reduced to a small number in a generated topology by our design methodology while maintaining network cost 50% less than that in standard tori topologies.

We present an automated lemma generation method for equational, inductive theorem proving based on the term rewriting induction of Reddy and Aoto as well as the divergence critic framework of Walsh. The method effectively works by using the divergence-detection technique to locate differences in diverging sequences, and generates potential lemmas automatically by analyzing these differences. We have incorporated this method in the multi-context inductive theorem prover of Sato and Kurihara to overcome the strategic problems resulting from the unsoundness of the method. The experimental results show that our method is effective especially for some problems diverging with complex differences (i.e., parallel and nested differences).

In this study, we propose a statistical reputation approach for constructing a reliable packet route in ad-hoc sensor networks. The proposed method uses reputation as a measurement for router node selection through which a reliable data route is constructed for packet delivery. To refine the reputation, a transaction density is defined here to showcase the influence of node transaction frequency over the reputation. And to balance the energy consumption and avoid choosing repetitively the same node with high reputation, node remaining energy is also considered as a reputation factor in the selection process. Further, a shortest-path-tree routing protocol is designed so that data packets can reach the base station through the minimum intermediate nodes. Simulation tests illustrate the improvements in the packet delivery ratio and the energy utilization.