This paper improves radiation patterns and impedance matching of a broadband sleeve dipole antenna. A broadband sleeve dipole antenna is designed and the effect of the structure parameters on the |S11| characteristics is calculated. Current distributions of the resonance frequencies are calculated. A broadband sleeve dipole antenna with plate element is proposed. Better impedance matching is obtained by adjusting the size of the plate element. The nulls of the radiation patterns are reduced at high frequencies and the gain in the horizontal direction is improved.

Stochastic resonance can improve the signal-to-noise ratio of digital baseband signals. However, the output of SR system needs some time for evolution to achieve global steady-state. This paper first analyzes the evolution time of SR systems, which is an important factor for digital baseband signal processing based on SR. This investigation shows that the sampling number per symbol should be rather large, and the minimum sampling number per symbol is deduced according to the evolution time of SR system.

This paper studies a wireless powered communication network (WPCN) with non-orthogonal multiple access (NOMA) under successive interference cancellation (SIC) constraints, where the users first harvest energy from the power station and then transmit data to the information receiver simultaneously. Under this setup, we investigate the system throughput maximization problem. We first formulate an optimization problem for a general case, which is non-convex. To derive the optimal solution, new variables are introduced to transform the initial problem into a convex optimization problem. For a special case, i.e., two-user case, the optimal solution is derived as a closed-form expression. Simulations on the effect of SIC constraints show the importance of the distinctness among users' channels for the proposed model.

Performance based on multi-party discussion has been reported to be superior to that based on individuals. However, it is impossible that all participants simultaneously express opinions due to the time and space limitations in a large-scale discussion. In particular, only a few representative discussants and audiences can speak in conventional unidirectional discussions (e.g., panel discussion), although many participants gather for the discussion. To solve these problems, in this study, we proposed a cyber-physical discussion using “COLLAGREE,” which we developed for building consensus of large-scale online discussions. COLLAGREE is equipped with functions such as a facilitator, point ranking system, and display of discussion in tree structure. We focused on the relationship between satisfaction with the discussion and participants' desire to express opinions. We conducted the experiment in the panel discussion of an actual international conference. Participants who were audiences in the floor used COLLAGREE during the panel discussion. They responded to questionnaires after the experiment. The main findings are as follows: (1) Participation in online discussion was associated with the satisfaction of the participants; (2) Participants who desired to positively express opinions joined the cyber-space discussion; and (3) The satisfaction of participants who expressed opinions in the cyber-space discussion was higher than those of participants who expressed opinions in the real-space discussion and those who did not express opinions in both the cyber- and real-space discussions. Overall, active behaviors in the cyber-space discussion were associated with participants' satisfaction with the entire discussion, suggesting that cyberspace provided useful alternative opportunities to express opinions for audiences who used to listen to conventional unidirectional discussions passively. In addition, a complementary relationship exists between participation in the cyber-space and real-space discussions. These findings can serve to create a user-friendly discussion environment.

Due to the structure complexity, it is difficult to display structure of large-scale network fully. To solve the problem, this paper research on network simplification and accelerating drawing. Specific research content includes accelerated network layout based on quadtree and community geometric constrain, aiming to provide overall situation perception of network topology. Experiment results show that this method can quickly visualize complex structure of large-scale network, and present overall situation and structural characteristics of the network by clear and understandable visual expression, and contribute to mining and awareness of network connection mode and structural characteristics.

Recently, the join processing of large-scale datasets in MapReduce environments has become an important issue. However, the existing MapReduce-based join algorithms suffer from too much overhead for constructing and updating the data index. Moreover, the similarity computation cost is high because the existing algorithms partition data without considering the data distribution. In this paper, we propose two grid-based join algorithms for MapReduce. First, we propose a similarity join algorithm that evenly distributes join candidates using a dynamic grid index, which partitions data considering data density and similarity threshold. We use a bottom-up approach by merging initial grid cells into partitions and assigning them to MapReduce jobs. Second, we propose a k-NN join query processing algorithm for MapReduce. To reduce the data transmission cost, we determine an optimal grid cell size by considering the data distribution of randomly selected samples. Then, we perform kNN join by assigning the only related join data to a reducer. From performance analysis, we show that our similarity join query processing algorithm and our k-NN join algorithm outperform existing algorithms by up to 10 times, in terms of query processing time.

Recently, the opportunity to discuss topics on a variety of online discussion bulletin boards has been increasing. However, it can be difficult to understand the contents of each discussion as the number of posts increases. Therefore, it is important to generate headlines that can automatically summarize each post in order to understand the contents of each discussion at a glance. In this paper, we propose a method to extract and generate post headlines for online discussion bulletin boards, automatically. We propose templates with multiple patterns to extract important sentences from the posts. In addition, we propose a method to generate headlines by matching the templates with the patterns. Then, we evaluate the effectiveness of our proposed method using questionnaires.

The intermediate frequency-over-fiber (IFoF) technology has attracted attention as an alternative transmission scheme to the functional split for the next-generation mobile fronthaul links due to its high spectral efficiency and perfect centralized control ability. In this paper, we discuss and clarify network architectures suited for IFoF, based on its advantages over the functional split. One of the major problems for IFoF transmission is dispersion-induced RF power fading, which limits capacity and transmission distance. We introduce our previous work, in which high-capacity and long-distance IFoF transmission was demonstrated by utilizing a parallel intensity/phase modulators (IM/PM) transmitter which can effectively avoid the fading. The IFoF technology with the proposed scheme is well suited for the long-distance mobile fronthaul links for the 5th generation (5G) mobile system and beyond.

This paper proposes the mesh-topology based wireless-powered communication network (MT-WPCN), which consists of a hybrid-access point (H-AP) and nodes. The H-AP broadcasts energy to all nodes by wireless, and the nodes harvest the energy and then communicate with other nodes including the H-AP. For the communication in the MT-WPCN, we propose the harvest-then-transceive protocol to ensure that the nodes can harvest energy from the H-AP and transmit information selectively to the H-AP or other nodes, which is not supported in most protocols proposed for the conventional WPCN. In the proposed protocol, we consider that the energy harvesting can be interrupted at nodes, since the nodes cannot harvest energy during transmission or reception. We also consider that the harvested energy is consumed by the reception of information from other nodes. In addition, the energy reservation model is required to guarantee the QoS, which reserves the infimum energy to receive information reliably by the transmission power control. Under these considerations, first, we design the half harvest-then-transceive protocol, which indicates that a node transmits information only to other nodes which do not transmit information yet, for investing the effect of the energy harvesting interruption. Secondly, we also design the full harvest-then-transceive protocol for the information exchange among nodes and compatibility with the conventional star-topology based WPCN, which indicates that a node can transmit information to any network unit, i.e., the H-AP and all nodes. We study the sum-throughput maximization in the MT-WPCN based on the half and full harvest-then-transceive protocols, respectively. Furthermore, the amount of harvested energy is analytically compared according to the energy harvesting interruption in the protocols. Simulation results show that the proposed MT-WPCN outperforms the conventional star-topology based WPCN in terms of the sum-throughput maximization, when wireless information transmission among nodes occurs frequently.

In this paper, a new array geometry is proposed which is capable of performing underdetermined Direction-Of-Arrival (DOA) estimation for the circular array configuration. DOA estimation is a classical problem and one of the most important techniques in array signal processing as it has applications in wireless and mobile communications, acoustics, and seismic sensing. We consider the problem of estimating DOAs in the case when we have more sources than the number of physical sensors where the resolution must be maintained. The proposed array geometry called Nested Sparse Circular Array (NSCA) is an extension of the two level nested linear array obtained by nesting two sub-circular arrays and one element is placed at the origin. In order to extend the array aperture, a Khatri-Rao (KR) approach is applied to the proposed NSCA which yields the virtual array structure. To utilize the increase in the degrees of freedom (DOFs) that this new array provides, a subspace based approach (MUSIC) for DOA estimation and l1-based optimization approach is extended to estimate DOAs using NSCA. Simulations show that better performance for underdetermined DOA estimation is achieved using the proposed array geometry.

Massive multiple-input and multiple-output (MIMO) is a key technology to meet the increasing capacity demands that must be satisfied by next generation wireless systems. However, it is expensive to use linear power amplifiers when implementing a massive MIMO system as it will have hundreds of antennas. In this paper, considering that low peak-to-average power ratio (PAPR) of transmit signals can facilitate hardware-friendly equipment with nonlinear but power-efficient amplifiers, we first formulate the precoding scheme as a PAPR minimization problem. Then, in order to obtain the optimal solution with low complexity, the precoding problem is recast into a Bayesian estimation problem by leveraging belief propagation algorithm. Eventually, we propose a low-PAPR approximate message passing (LP-AMP) algorithm based on belief propagation to ensure the good transmission performance and minimize the PAPR to realize practical deployments. Simulation results reveal that the proposed method can get PAPR reduction and adequate transmission performance, simultaneously, with low computational complexity. Moreover, the results further indicate that the proposed method is suitable for practical implementation, which is appealing for massive multiuser MIMO (MU-MIMO) systems.

This paper demonstrates the suppressing power of 10 Gbps On Off keyed signal using biased half-wave rectification. Authors have previously reported that radio frequency (RF) and optical on-off keying (OOK) signal can be simultaneously transmitted over the radio over fiber (RoF) link [1]. Since the optical OOK signal has much broader bandwidth compared to RF signal, it interferes with RF signal. Reference [1] experimentally shows that the optical OOK signal degrades the RF signal in terms of signal-to-noise power ratio (SNR) when 10 Gbps OOK and 1.9 GHz microwave are employed as baseband and RF, respectively. This paper proposes an interference suppression, and the proposal is subsequently used for detecting the RF signal. Experiments are conducted for the purpose of the proof-of-concept of the proposal. Finally numerical simulations are employed to show the performance enhancement in terms of error vector magnitude (EVM).

This paper presents a 27.5-29.6GHz fractional-N frequency synthesizer using reference and frequency doublers to achieve low in-band and out-of-band phase-noise for 5G mobile communications. A consideration of the baseband carrier recovery circuit helps estimate phase noise requirement for high modulation scheme. The push-push amplifier and 28GHz balun help achieving differential signals with low out-of-band phase noise while consuming low power. A charge pump with gated offset as well as reference doubler help reducing PD noise resulting in low in-band phase noise while sampling loop filter helps reduce spurs. The proposed synthesizer has been implemented in 65nm CMOS technology achieving an in-band and out-of-band phase noise of -78dBc/Hz and -126dBc/Hz, respectively. It consumes only a total power of 33mW. The jitter-power figure-of-merit (FOM) is -231dB which is the highest among the state of the art >20GHz fractional-N PLLs using a low reference clock (<200MHz). The measured reference spurs are less than -80dBc.

In the process of VLSI design, ECO (Engineering Change Order) may occur at any design phase. When ECO happens after the netlist is generated and optimized, designers may like to modify the netlist directly. This is because if ECO is performed in the high-level description, the netlist should be resynthesized and the result may be significantly different from the original one, even if the modification in the high-level description is small. As the result, the efforts spent on optimization so far may become useless. When the netlist is modified directly, the C description should be revised accordingly. This paper proposes a method to reconstruct a C description from the revised netlist. In the proposed method, designers need to provide a template represented in C, which has some vacant (blanked) places and is created from the original C description. The vacant places are automatically synthesized using a CEGIS-based method (Counter Example Guided Inductive Synthesis). Using a set of use-cases, our method tries to find the correct expressions for the vacant places so that the entire description becomes functionally equivalent to the given modified netlist, by only simulating the netlist. Experimental results show that the proposed method can reconstruct C descriptions successfully within practical time for several examples including the one having around 9,000 lines of executable statements. Moreover, the proposed method can be applied to equivalence checking between a netlist and a C description, as shown by our experimental results.

Investigative reports plagiarized from the web should be eliminated because such reports result in ineffective knowledge construction. In this study, we developed an investigative report writing support system for effective knowledge construction from the web. The proposed system attempts to prevent plagiarism by restricting copying and pasting information from web pages. With this system, students can verify information through web browsing, externalize their constructed knowledge as notes for report materials, write reports using these notes, and remove inadequacies in the report by reflection. A comparative experiment showed that the proposed system can potentially prevent web page plagiarism and make knowledge construction from the web more effective compared to a conventional report writing environment.

Online chat systems, e.g.., Twitter and Slack, have been used in academic conferences or study meetings as a means of instant discussion and sharing related information alongside a real presentation. We propose a system for activating online discussion by providing a bot that suggests webpages related to current timeline of the discussion. Our system generates keyword vectors according to discussion timeline, searches best related webpages from several web sites, and timely provides these pages to the discussion timeline. This paper describes deployments of our system in two types of meetings: lightning talk format meetings and group meetings; and daily exchanges using online chat system. As a result, we could not find good enough reactions to the bot's postings from meeting participants at the lightning talk format meetings, but we could observe more reactions and progress of discussion caused by the bot's postings at the relaxed meetings and daily exchanges among group members.

The impedance expansion method (IEM), which was previously proposed by the authors, is a circuit-modeling technique for electrically-very-small devices. The equivalent circuits derived by the IEM include dependent voltage sources proportional to the powers of the frequency. However, the previous report did not describe how circuit simulators could realize such dependent voltage sources. This paper shows how this can be achieved by approximating the equivalent circuit using only passive elements.

This work presents a hybrid formulation of the stochastic reduced order model (SROM) algorithm, which makes use of Gauss quadrature, a key ingredient of the stochastic collocation method, to avoid the cumbersome optimization process required by SROM for optimal extraction of the sample set. With respect to classic SROM algorithms, the proposed formulation allows a significant reduction in computation time and burden as well as a remarkable improvement in the accuracy and convergence rate in the estimation of statistical moments. The method is here applied to a specific case study, that is the prediction of crosstalk in a two-conductor wiring structure with electrical and geometrical parameters not perfectly known. Both univariate and multivariate analyses are carried out, with the final objective being to compare the performance of the two SROM formulations with respected to Monte Carlo simulations.

In this paper, we investigate the capacity performance of an in-band full-duplex (IBFD) amplify-and-forward two-way relay system under the effect of residual loop-back-interference (LBI). In a two-way IBFD relay system, two IBFD nodes exchange data with each other via an IBFD relay. Both two-way relaying and IBFD one-way relaying could double the spectrum efficiency theoretically. However, due to imperfect channel estimation, the performance of two-way relaying is degraded by self-interference at the receiver. Moreover, the performance of the IBFD relaying is deteriorated by LBI between the transmit antenna and the receive antenna of the node. Different from the IBFD one-way relay scenario, the IBFD two-way relay system will suffer from an extra level of LBI at the destination receiver. We derive accurate approximations of the average end-to-end capacities for both the IBFD and half-duplex modes. We evaluate the impact of the LBI and channel estimation errors on system performance. Monte Carlo simulations verify the validity of analytical results. It can be shown that with certain signal-to-noise ratio values and effective interference cancellation techniques, the IBFD transmission is preferable in terms of capacity. The IBFD two-way relaying is an attractive technique for practical applications.

Developing a robust appearance model is a challenging task due to appearance variations of objects such as partial occlusion, illumination variation, rotation and background clutter. Existing tracking algorithms employ linear combinations of target templates to represent target appearances, which are not accurate enough to deal with appearance variations. The underlying relationship between target candidates and the target templates is highly nonlinear because of complicated appearance variations. To address this, this paper presents a regularized kernel representation for visual tracking. Namely, the feature vectors of target appearances are mapped into higher dimensional features, in which a target candidate is approximately represented by a nonlinear combination of target templates in a dimensional space. The kernel based appearance model takes advantage of considering the non-linear relationship and capturing the nonlinear similarity between target candidates and target templates. l2-regularization on coding coefficients makes the approximate solution of target representations more stable. Comprehensive experiments demonstrate the superior performances in comparison with state-of-the-art trackers.