Network-listening-based synchronization is recently attracting attention as an effective timing synchronization method for indoor small-cell base stations as they cannot utilize GPS-based synchronization. It uses only the macro-cell downlink signal to establish synchronization with the overlaying macro cell. However, the loop-back signal from the small-cell base station itself interferes with the reception of the macro-cell downlink signal in the deployment of co-channel heterogeneous networks. In this paper, we investigate a synchronization method that avoids loop-back interference by muting small-cell data transmission and shifting small-cell transmission timing. Our proposal enables to reduce the processing burden of the network listening and mitigate the throughput degradation of the small cell caused by the data-transmission mutation. In addition to this, the network-listening system enables the network listening in dense small cell deployments where a large number of neighboring small cells exist. We clarify the performance of our proposal by computer simulations and laboratory experiments on actual equipment.

Peer-to-peer overlay networks can easily achieve a large-scale content sharing system on the Internet. Although unstructured peer-to-peer networks are suitable for finding entire partial-match content, flooding-based search is an inefficient way to obtain target content. When the shared content is semantically specified by a great number of attributes, it is difficult to derive the semantic similarity of peers beforehand. This means that content search methods relying on interest-based locality are more advantageous than those based on the semantic similarity of peers. Existing search methods that exploit interest-based locality organize multiple peer groups, in each of which peers with common interests are densely connected using short-cut links. However, content searches among multiple peer groups are still inefficient when the number of incident links at each peer is limited due to the capacity of the peer. This paper proposes a novel content search method that exploits interest-based locality. The proposed method can organize an efficient peer-to-peer network similar to the semantic small-world random graph, which can be organized by the existing methods based on the semantic similarity of peers. In the proposed method, topology transformation based on local link replacement maintains the numbers of incident links at all the peers. Simulation results confirm that the proposed method can achieve a significantly higher ratio of obtainable partial-match content than existing methods that organize peer groups.

In this paper, we present a small, wide-band, Inverted-L Antenna (ILA) with non-Foster matching. The antenna's size is 9.5×19.5mm2 and it is integrated on a Printed Circuit Board (PCB) of 90×35mm2. A design procedure is presented and sensitivity and stability analysis are performed. Experiments show that the non-Foster matched antenna has (S11 < -10dB) impedance bandwidth of 92.2% at a central frequency of 1.5GHz, whereas the passive antenna (without the non-Foster matching) has an impedance bandwidth of 12.6% at 2.46GHz.

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.

Small delay caused by a resistive open is difficult to test since circuit delay varies depending on various factors such as process variations and crosstalk even in fault-free circuits. We consider the problem of discriminating a resistive open by anomaly detection using delay distributions obtained by the effect of various input signals provided to adjacent lines. We examined the circuit delay in a fault-free circuit and a faulty circuit by applying electromagnetic simulator and circuit simulator for a line structure with adjacent lines under consideration of process variations. The effectiveness of the method that discriminates a resistive open is shown for the results obtained by the simulation.

This paper presents a strategy, Weighted Voting of Discriminative Regions (WVDR), to improve the face recognition performance, especially in Small Sample Size (SSS) and occlusion situations. In WVDR, we extract the discriminative regions according to facial key points and abandon the rest parts. Considering different regions of face make different contributions to recognition, we assign weights to regions for weighted voting. We construct a decision dictionary according to the recognition results of selected regions in the training phase, and this dictionary is used in a self-defined loss function to obtain weights. The final identity of test sample is the weighted voting of selected regions. In this paper, we combine the WVDR strategy with CRC and SRC separately, and extensive experiments show that our method outperforms the baseline and some representative algorithms.

We proposed a new architecture of antenna, transmitter and receiver feeding configuration for small synthetic aperture radar (SAR) that is compatible with 100kg class satellite. Promising applications are constellations of earth observations together with optical sensors, and responsive, disaster monitoring missions. The SAR antenna is a deployable, passive, honeycomb panel antenna with slot array that can be stowed compactly. RF (radio frequency) instruments are in a satellite body and RF signal is fed to a deployable antenna through non-contacting choke flanges at deployable hinges. This paper describes its development strategy and the present development status of the small spaceborne SAR based on this architecture.

This paper presents the design and experimental evaluation of 60GHz small cell radio access based on IEEE 802.11ad/WiGig. The access point (AP) prototype used combines three RF modules with beamforming technology to provide 360° area coverage. In order to compensate for limited communication distance, multiple APs are employed to achieve wide area coverage. A handover algorithm suitable for IEEE 802.11ad/WiGig is employed to achieve flexible control of the cell coverage of each AP. As a proof of concept, a prototype system is set up at Narita International Airport and the capability of multiuser Gb/s wireless access is successfully demonstrated. In addition, the system behavior under stringent conditions is evaluated by load testing and throughput degradation due to co-channel and inter-channel interference is investigated.

Small group detection is still a challenging problem in crowds. Traditional methods use the trajectory information to measure pairwise similarity which is sensitive to the variations of group density and interactive behaviors. In this paper, we propose two types of information by simultaneously incorporating trajectory and interaction information, to detect small groups in crowds. The trajectory information is used to describe the spatial proximity and motion information between trajectories. The interaction information is designed to capture the interactive behaviors from video sequence. To achieve this goal, two classifiers are exploited to discover interpersonal relations. The assumption is that interactive behaviors often occur in group members while there are no interactions between individuals in different groups. The pairwise similarity is enhanced by combining the two types of information. Finally, an efficient clustering approach is used to achieve small group detection. Experiments show that the significant improvement is gained by exploiting the interaction information and the proposed method outperforms the state-of-the-art methods.

This paper introduces a base station antenna system as a future cellular technology. The base station antenna system is the key to achieving high-speed data transmission. It is particularly important to improve the frequency reuse factor as one of the roles of a base station. Furthermore, in order to solve the interference problem due to the same frequency being used by the macro cell and the small cell, the author focuses on beam and null control using an AAS (Active Antenna System) and elucidates their effects through area simulations and field tests. The results showed that AAS can improve the SINR (signal to interference-plus-noise ratio) of the small cell area inside macro cells. The paper shows that cell quality performance can be improved by incorporating the AAS into a cellular base station as its antenna system for beyond 4G radio access technology including the 5G cellular system.

An interference-aware dynamic channel assignment scheme is proposed with consideration of co-tier interference for the downlink of an OFDMA/FDD based dense small-cell network. The proposed scheme adaptively assigns subchannels to the small-cell user equipment (SUE) according to the given traffic load and interference effect from neighbor small-cell access points. The simulation results show that the proposed scheme outperforms the other schemes based on the graph coloring algorithm in terms of the mean SUE capacity.

Theoretical maximum radiation efficiency of electrically small spherical surface antennas has been derived in this study. The current on the antenna surface is described in terms of vector spherical harmonics, and the radiated and the dissipated powers are calculated to obtain the radiation efficiency. It has been found that non-resonant TM1m mode shows the best radiation efficiency, and a proper combination of TM10 and TE10 modes establishes a resonant spherical surface antenna whose radiation efficiency is bounded by those values of non-resonant TM10 and TE10 modes. As a practical example of the spherical surface antennas, the radiation efficiency of the spherical helix antennas has also been computed to check the validity of our formulation.

In 1999, Boneh and Durfee introduced the small inverse problem, which solves the bivariate modular equation x(N+y)≡1(mod e. Absolute values of solutions for x and y are bounded above by X=Nδ and Y=Nβ, respectively. They solved the problem for β=1/2 in the context of small secret exponent attacks on RSA and proposed a polynomial time algorithm that works when δ<(7-2√7)/6≈0.284. In the same work, the bound was further improved to δ<1-1/≈2≈0.292. Thus far, the small inverse problem has also been analyzed for an arbitrary β. Generalizations of Boneh and Durfee's lattices to obtain the stronger bound yielded the bound δ<1-≈β. However, the algorithm works only when β≥1/4. When 0<β<1/4, there have been several works where the authors claimed their results are the best. In this paper, we revisit the problem for an arbitrary β. At first, we summarize the previous results for 0<β<1/4. We reveal that there are some results that are not valid and show that Weger's algorithms provide the best bounds. Next, we propose an improved algorithm to solve the problem for 0<β<1/4. Our algorithm works when δ<1-2(≈β(3+4β)-β)/3. Our algorithm construction is based on the combinations of Boneh and Durfee's two forms of lattices and it is more natural compared with previous works. For the cryptographic application, we introduce small secret exponent attacks on Multi-Prime RSA with small prime differences.

This paper proposes a multiband automatic tunable antenna system for wide frequency bands of 704-2690MHz for cellular wireless communication systems. The proposed system controls variable capacitors connected between the antenna and a transmitter based on the received power of a probe. Locating the probe near the tip of the antenna enables frequency-a operation. The antenna is a multiband two-arm monopole antenna printed on a 60mm × 10mm area of a 60mm × 100mm FR-4 printed circuit board (PCB). The probe is a small dipole antenna capacitively coupled with the antenna. Fine-tuning based on simple hill-climbing optimization compensates the mismatch due to the surroundings, e.g., a user's hand/head or desk assuming channel-informed rough-tuning beforehand. A prototype consisting of varicap diodes and some other devices demonstrates automatic tunability.

In a network with dense deployment of multiple-input multiple-output (MIMO) small cells, coverage overlap between the small cells produces intercell-interference, which degrades system capacity. This paper proposes an intercell-interference management (IIM) scheme that aims to maximize system capacity by using both power control for intercell-interference coordination (ICIC) on the transmitter side and interference cancellation (IC) on the receiver side. The power control determines transmit power levels at the base stations (BSs) by employing a neural network (NN) algorithm over the backhaul. To further improve the signal to interference plus noise ratio (SINR), every user terminal (UT) employs a multiuser detector (MUD) as IC. The MUD detects not only the desired signals, but also some interfering signals to be cancelled from received signals. The receiver structure consists of branch metric generators (BMGs) and MUD. BMGs suppress residual interference and noise in the received signals by whitening matched filters (WMFs), and then generate metrices by using the WMFs' outputs and symbol candidates that the MUD provides. On the basis of the metrices, the MUD detects both the selected interfering signals and the desired signals. In addition, the MUD determines which interfering signals are detected by an SINR based replica selection algorithm. Computer simulations demonstrate that the SINR based replica selection algorithm, which is combined with channel encoders and packet interleavers, can significantly improve the system bit error rate (BER) and that combining IC at the receiver with NN power control at the transmitter can considerably increase the system capacity. Furthermore, it is shown that choosing the detected interfering signals by the replica selection algorithm can obtain system capacity with comparable loss and less computational complexity compared to the conventional greedy algorithm.

This paper proposes a Watts and Strogatz-model based routing method for wireless sensor network along with link-exchange operation. The proposed routing achieves low data-collection delay because of hub-node existence. By applying the link exchanges, node with low remaining battery level can escape from a hub node. Therefore, the proposed routing method achieves the fair battery-power consumptions among sensor nodes. It is possible for the proposed method to prolong the network lifetime with keeping the small-world properties. Simulation results show the effectiveness of the proposed method.

We investigate a phased array-fed dual reflector antenna applying one-dimensional beam-scanning of the center-fed type, using an elliptical aperture to provide wide area observation. The distinguishing feature of this antenna is its elliptical aperture shape, in which the aperture diameter differs between the forward satellite direction and the cross-section orthogonal to it. The shape in the plane of the forward satellite direction, which does not have a beam-scanning function, is a ring-focus Cassegrain antenna, and the shape in the plane orthogonal to that, which does have a beam-scanning function, is an imaging reflector antenna. This paper describes issues which arose during design of the elliptical aperture shape and how they were solved, and presents design results using elliptical aperture dimensions of 1600 mm × 600 mm, in which the beam width differs by more than two times in the orthogonal cross-section. The effectiveness of the antenna was verified by fabricating a prototype antenna based on the design results. Measurement results confirmed that an aperture efficiency of 50% or more could be achieved, and that a different beam width was obtained in the orthogonal plane in accordance with design values.

This study focuses on modeling the storytelling performance of the participants in a group conversation. Storytelling performance is one of the fundamental communication techniques for providing information and entertainment effectively to a listener. We present a multimodal analysis of the storytelling performance in a group conversation, as evaluated by external observers. A new multimodal data corpus is collected through this group storytelling task, which includes the participants' performance scores. We extract multimodal (verbal and nonverbal) features regarding storytellers and listeners from a manual description of spoken dialog and from various nonverbal patterns, including each participant's speaking turn, utterance prosody, head gesture, hand gesture, and head direction. We also extract multimodal co-occurrence features, such as head gestures, and interaction features, such as storyteller utterance overlapped with listener's backchannel. In the experiment, we modeled the relationship between the performance indices and the multimodal features using machine-learning techniques. Experimental results show that the highest accuracy (R2) is 0.299 for the total storytelling performance (sum of indices scores) obtained with a combination of verbal and nonverbal features in a regression task.

The random deployment of small cell base stations (BSs) causes the coverage areas of neighboring cells to overlap, which increases intercell interference and degrades the system capacity. This paper proposes a new intercell interference management (IIM) scheme to improve the system capacity in multiple-input multiple-output (MIMO) small cell networks. The proposed IIM scheme consists of both an interference cancellation (IC) technique on the receiver side, and a neural network (NN) based power control algorithm for intercell interference coordination (ICIC) on the transmitter side. In order to improve the system capacity, the NN power control optimizes downlink transmit power while IC eliminates interfering signals from received signals. Computer simulations compare the system capacity of the MIMO network with several ICIC algorithms: the NN, the greedy search, the belief propagation (BP), the distributed pricing (DP), and the maximum power, all of which can be combined with IC reception. Furthermore, this paper investigates the application of a multi-layered NN structure called deep learning and its pre-training scheme, into the mobile communication field. It is shown that the performance of NN is better than that of BP and very close to that of greedy search. The low complexity of the NN algorithm makes it suitable for IIM. It is also demonstrated that combining IC and sectorization of BSs acquires high capacity gain owing to reduced interference.

System expandability becomes a major concern for highly parallel computers and data centers, because their number of nodes gradually increases year by year. In this context we propose a low-degree topology and its floor layout in which a cabinet or node set can be newly inserted by connecting short cables to a single existing cabinet. Our graph analysis shows that the proposed topology has low diameter, low average shortest path length and short average cable length comparable to existing topologies with the same degree. When incrementally adding nodes and cabinets to the proposed topology, its diameter and average shortest path length increase modestly. Our discrete-event simulation results show that the proposed topology provides a comparable performance to 2-D Torus for some parallel applications. The network cost and power consumption of DSN-F modestly increase when compared to the counterpart non-random topologies.