Block-state realization of state-space digital filters offers reduced implementation complexity relative to canonical state-space filters while filter's internal structure remains accessible. In this paper, we present a quantitative analysis on l2 coefficient sensitivity of block-state digital filters. Based on this, we develop two techniques for minimizing average l2-sensitivity subject to l2-scaling constraints. One of the techniques is based on a Lagrange function and some matrix-theoretic techniques. The other solution method converts the problem at hand into an unconstrained optimization problem which is solved by using an efficient quasi-Newton algorithm where the key gradient evaluation is done in closed-form formulas for fast and accurate execution of quasi-Newton iterations. A case study is presented to demonstrate the validity and effectiveness of the proposed techniques.

In this letter, we study a scenario based on decoupled RF energy harvesting networks (DRF-EHNs) that separate energy sources from information sources to overcome the doubly near-far problem and improve harvesting efficiency. We propose an algorithm to maximize energy efficiency (EE) while satisfying constraints on the maximum transmit power of the hybrid access point (H-AP) and power beacon (PB), while further satisfying constraints on the minimum quality of service and minimum amount of harvested power in multi-user Rayleigh fading channel. Using nonlinear fractional programming and Lagrangian dual decomposition, we optimize EE with four optimization arguments: the transmit power from the H-AP and PB, time-splitting ratio, and power-splitting ratio. Numerical results show that the proposed algorithm is more energy-efficient compared to baseline schemes.

In this work, the metal-oxide-metal (MOM) capacitor in the scaled CMOS process has been modeled at high frequencies using an EM simulator, and its layout has been optimized. The modeled parasitic resistance consists of four components, and the modeled parasitic inductance consists of the comb inductance and many mutual inductances. Each component of the parasitic resistance and inductance show different degrees of dependence on the finger length and on the number of fingers. The substrate network parameters also have optimum points. As such, the geometric dependence of the characteristics of the MOM capacitor is investigated and the optimum layout in the constant-capacitance case is proposed by calculating the results of the model. The proposed MOM capacitor structures for 50fF at f =60GHz are L =5μm with M =3, and, L =2μm with M =5 and that for 100fF at f =30GHz are L =9μm with M =3, and L =4μm with M =5. The target process is 65-nm CMOS.

This research addresses improvements in the efficiency of spectrum utilization by defending against jamming attacks and corrupting the communications of the adversary network by executing its own jamming strategy. The proposed scheme, based on game theory, selects the best operational strategy (i.e., communications and jamming strategies) to maximize the successful communications and jamming rates of the network. Moreover, an estimation algorithm is investigated to predict the behavior of the adversary network in order to improve the efficiency of the proposed game theory-based scheme.

Precise determination of antenna phase centers is crucial to reduce the uncertainty in gain when employing the three-antenna method, particularly when the range distances are short-such as a 3-m radio anechoic chamber, where the distance between the phase centers and the open ends of an aperture antenna (the most commonly-used reference) is not negligible compared with the propagation distance. An automatic system to determine the phase centers of aperture antennas in a radio anechoic chamber is developed. In addition, the absolute gain of horn antennas is evaluated using the three-antenna method. The phase centers of X-band pyramidal horns were found to migrate up to 18mm from the open end. Uncertainties in the gain were evaluated in accordance with ISO/IEC Guide 93-3: 2008. The 95% confidence interval of the horn antenna gain was reduced from 0.57 to 0.25dB, when using the phase center location instead of the open end. The phase centers, gains, polarization, and radiation patterns of space-borne antennas are measured: low and medium-gain X-band antennas for an ultra small deep space probe employing the polarization pattern method with use of the horn antenna. The 95% confidence interval in the antenna gain decreased from 0.74 to 0.47dB.

In this paper, we propose an indoor localization method that uses only the Received Signal Strength Indicator (RSSI) of signals transmitted from wireless beacons. The beacons use three-element array antennas, and the position of the receiving terminal is estimated by using multiple DOD information. Each beacon transmits four beacon signals with different directivities by feeding signals to the three-element array antennas via 180-degree and 90-degree hybrids. The correlation matrix of the propagation channels is estimated from just the strength of the signals, and the DOD is estimated from the calculated correlation matrix. For determining the location of the receiving terminal, the existence probability function is introduced. Experiments show that the proposed method attains lower position estimation error than the conventional method.

Wireless Sensor Networks (WSNs) are randomly deployed in a hostile environment and left unattended. These networks are composed of small auto mouse sensor devices which can monitor target information and send it to the Base Station (BS) for action. The sensor nodes can easily be compromised by an adversary and the compromised nodes can be used to inject false vote or false report attacks. To counter these two kinds of attacks, the Probabilistic Voting-based Filtering Scheme (PVFS) was proposed by Li and Wu, which consists of three phases; 1) Key Initialization and assignment, 2) Report generation, and 3) En-route filtering. This scheme can be a successful countermeasure against these attacks, however, when one or more nodes are compromised, the re-distribution of keys is not handled. Therefore, after a sensor node or Cluster Head (CH) is compromised, the detection power and effectiveness of PVFS is reduced. This also results in adverse effects on the sensor network's lifetime. In this paper, we propose a Fuzzy Rule-based Key Redistribution Method (FRKM) to address the limitations of the PVFS. The experimental results confirm the effectiveness of the proposed method by improving the detection power by up to 13.75% when the key-redistribution period is not fixed. Moreover, the proposed method achieves an energy improvement of up to 9.2% over PVFS.

Two different types of representations, such as an image and its manually-assigned corresponding labels, generally have complex and strong relationships to each other. In this paper, we represent such deep relationships between two different types of visible variables using an energy-based probabilistic model, called a deep relational model (DRM) to improve the prediction accuracies. A DRM stacks several layers from one visible layer on to another visible layer, sandwiching several hidden layers between them. As with restricted Boltzmann machines (RBMs) and deep Boltzmann machines (DBMs), all connections (weights) between two adjacent layers are undirected. During maximum likelihood (ML) -based training, the network attempts to capture the latent complex relationships between two visible variables with its deep architecture. Unlike deep neural networks (DNNs), 1) the DRM is a totally generative model and 2) allows us to generate one visible variables given the other, and 2) the parameters can be optimized in a probabilistic manner. The DRM can be also fine-tuned using DNNs, like deep belief nets (DBNs) or DBMs pre-training. This paper presents experiments conduced to evaluate the performance of a DRM in image recognition and generation tasks using the MNIST data set. In the image recognition experiments, we observed that the DRM outperformed DNNs even without fine-tuning. In the image generation experiments, we obtained much more realistic images generated from the DRM more than those from the other generative models.

Japan Broadcasting Corporation (NHK) started test satellite broadcasting of ultra-high-definition television (UHDTV) on August 1st, 2016. The test broadcasting is being provided in the 12-GHz (11.7 to 12.75GHz) band with right-hand circular polarization. In 2018, left-hand circular polarization in the same frequency band will be used for satellite broadcasting of UHDTV. Because UHDTV satellite broadcasting uses the 16APSK modulation scheme, which requires a higher carrier-to-noise ratio than that used for HDTV in Japan, it is important to mitigate the cross-polarization interference. Therefore, we fabricated and tested a dual-circularly polarized offset parabolic reflector antenna that has a feed antenna composed of a 2×2 microstrip antenna array, which is sequentially rotated to enhance the polarization purity. Measured results showed that the fabricated antenna complied with our requirements, a voltage standing wave ratio of less than 1.4, antenna gain of 34.5dBi (i.e., the aperture efficiency was 69%), and cross-polarization discrimination of 28.7dB.

In this paper, we propose a new structure for a compact matched filter bank (MFB) for an optical zero-correlation zone (ZCZ) sequence set with Zcz=2z. The proposed MFB can reduces operation elements such as 2-input adders and delay elements. The number of 2-input adders decrease from O(N2) to O(N log2 N), delay elements decrease from O(N2) to O(N). In addition, the proposed MFBs for the sequence of length 32, 64, 128 and 256 with Zcz=2,4 and 8 are implemented on a field programmable gate array (FPGA). As a result, the numbers of logic elements (LEs) of the proposed MFBs for the sequences with Zcz=2 of length 32, 64, 128 and 256 are suppressed to about 76.2%, 84.2%, 89.7% and 93.4% compared to that of the conventional MFBs, respectively.

As an effective method, exponential discriminant analysis (EDA) has been proposed and widely used to solve the so-called small-sample-size (SSS) problem. In this paper, a simple and effective generalization of EDA is presented and named as GEDA. In GEDA, a general exponential function, where the base of exponential function is larger than the Euler number, is used. Due to the property of general exponential function, the distance between samples belonging to different classes is larger than that of EDA, and then the discrimination property is largely emphasized. The experiment results on the Extended Yale and CMU-PIE face databases show that, GEDA gets more advantageous recognition performance compared to EDA.

We propose a wideband antenna that has both vertical and horizontal polarization to create access points with enhanced connectivity. The antenna is composed of a rectangular plate and a ground plate, and the rectangular plate is fed sideways from the ground plate. Its -10dB fractional bandwidth is approximately 162%. It is shown that the offset feed of the rectangular plate is important to attain wideband impedance matching and vertical polarized wave. The results of a parametric study to characterize the first- and second-lowest resonant frequencies are presented. Moreover, the behavior of the impedance matching and polarization is interpreted by dividing the current distribution around the feed port on the rectangular plate into the same direction current mode and the opposite direction current mode. The measured results for the return loss and the radiation pattern of a prototype antenna agree well with the simulation results, therefore the wideband property was experimentally confirmed.

Space optical communication has been considered one of the major candidates for high-rate data transmission and it reaches the practical stage to operate as a high-rate data transmission system. In this paper, the author reports the latest situation of space optical communication around the world, flight demonstrations, technological research and standardization. Research and development activities at Japan aerospace exploration agency (JAXA) are also presented.

Today's enterprise, data-center, and internet-service-provider networks deploy different types of network devices, including switches, routers, and middleboxes such as network address translation and firewalls. These devices are vertically integrated monolithic systems. Software-defined networking (SDN) and network function virtualization (NFV) are promising technologies for dis-aggregating vertically integrated systems into components by using “softwarization”. Software-defined networking separates the control plane from the data plane of switch and router, while NFV decouples high-layer service functions (SFs) or Network Functions (NFs) implemented in the data plane of a middlebox and enables the innovation of policy implementation by using SF chaining. Even though there have been several survey studies in this area, this area is continuing to grow rapidly. In this paper, we present a recent survey of this area. In particular, we survey research activities in the areas of re-architecting middleboxes, state management, high-performance platforms, service chaining, resource management, and trouble shooting. Efforts in these research areas will enable the development of future virtual-network-function platforms and innovation in service management while maintaining acceptable capital and operational expenditure.

The aim of this paper is to apply automatic jigsaw puzzle solvers, which are methods of assembling jigsaw puzzles, to the field of information security. Encryption-then-Compression (EtC) systems have been considered for the user-controllable privacy protection of digital images in social network services. Block scrambling-based encryption schemes, which have been proposed to construct EtC systems, have enough key spaces for protecting brute-force attacks. However, each block in encrypted images has almost the same correlation as that of original images. Therefore, it is required to consider the security from different viewpoints from number theory-based encryption methods with provable security such as RSA and AES. In this paper, existing jigsaw puzzle solvers, which aim to assemble puzzles including only scrambled and rotated pieces, are first reviewed in terms of attacking strategies on encrypted images. Then, an extended jigsaw puzzle solver for block scrambling-based encryption scheme is proposed to solve encrypted images including inverted, negative-positive transformed and color component shuffled blocks in addition to scrambled and rotated ones. In the experiments, the jigsaw puzzle solvers are applied to encrypted images to consider the security conditions of the encryption schemes.

The Smart City paradigm has become one of the most important research topics around the globe. Particularly in Europe, it is considered as a solution for the unstoppable increase of high density urban environments and the European Commission has included the Smart City research as one of the key objectives for the FP7 (Seventh Framework Program) and H2020 (Horizon 2020) research initiatives. As a result, a considerable amount of quality research, with particular emphasis on information and communication technologies, has been produced. In this paper, we review the current efforts dedicated in Europe to this research topic. Particular attention is paid in the review to the platforms and infrastructure technologies adopted to introduce the Internet of Things into the city, taking into account the constraints and harshness of urban environments. Furthermore, this paper also considers the efforts in the experimental perspective, which includes the review of existing Smart City testbeds, part of wider European initiatives such as FIRE (Future Internet Research and Experimentation) and FIWARE. Last but not least, the main efforts in providing interoperability between the different experimental facilities are also presented.

The demand for wireless traffic is increasing rapidly, which has posed huge challenges to mobile network operators (MNOs). A heterogeneous network (HetNet) framework, composed of a marcocell and femtocells, has been proved to be an effective way to cope with the fast-growing traffic demand. In this paper, we assume that both the macrocell and femtocells are owned by the same MNO, with revenue optimization as its ultimate goal. We aim to propose a pricing strategy for macro-femto HetNets with a user centric vision, namely, mobile users would have their own interest to make rational decisions on selecting between the macrocell and femtocells to maximize their individual benefit. We formulate a Stackelberg game to analyze the interactions between the MNO and users, and obtain the equilibrium solution for the Stackelberg game. Via extensive simulations, we evaluate the proposed pricing strategy in terms of its efficiency with respect to the revenue optimization.

In order to cope with severe interference in heterogeneous networks, this paper proposes a semi-blind interference cancellation scheme, which does not require multiple receive antennas or knowledge about training sequences of the interfering signals. The proposed scheme performs joint channel estimation and signal detection (JCESD) during the training period in order to blindly estimate channels of the interfering signals. On the other hand, maximum likelihood detection (MLD), which can be considered the optimum JCESD, must perform channel estimation for all transmitted signal candidates of the interfering signals and must search for the most likely signal candidate. Therefore, MLD incurs a prohibitive amount of computational complexity. To reduce such complexity drastically, the proposed scheme enhances the quantized channel approach, and applies the enhanced version to JCESD. In addition, a recalculation scheme is introduced to avoid inaccurate channel estimates due to local minima. Using the estimated channels, the proposed scheme performs multiuser detection (MUD) of the data sequences in order to cancel the interference. Computer simulations show that the proposed scheme outperforms a conventional scheme based on the Viterbi algorithm, and can achieve almost the same average bit error rate performance as the MUD with channels estimated from sufficiently long training sequences of both the desired signal and the interfering signals, while reducing the computational complexity significantly compared with full search involving all interfering signal candidates during the training period.

In recent years, software-defined networking (SDN), which performs centralized network management with software, has attracted much attention. Although packets are transmitted based on flow entries in SDN switches, the number of flow entries that the SDN switches can handle is limited. To overcome this difficulty, this paper proposes a flow-based routing method that performs flexible routing control with a small number of flow entries. The proposed method provides mixed integer programming. It assigns common paths to flows that can be aggregated at intermediate switches, while considering the utilization of network links. Because it is difficult for mixed integer programming to compute large-scale problems, the proposed method also provides a heuristic algorithm for them. Through numerical experiments, this paper shows that the proposed method efficiently reduces both the number of flow entries and the loads of congested links.

In this paper, we present a new three-way split formula for binary polynomial multiplication (PM) with five recursive multiplications. The scheme is based on a recently proposed multievaluation and interpolation approach using field extension. The proposed PM formula achieves the smallest space complexity. Moreover, it has about 40% reduced time complexity compared to best known results. In addition, using developed techniques for PM formulas, we propose a three-way split formula for Toeplitz matrix vector product with five recursive products which has a considerably improved complexity compared to previous known one.