In recent years, capsule endoscopy has attracted attention as one of the medical devices that examine internal digestive tracts without burdening patients. Wireless power transmission of the capsule endoscope has been researched now, and the power transmission efficiency can be improved by knowing the capsule location. In this paper, we develop a localization method wireless power transmission. Therefore, a simple algorithm for using received signal strength (RSS) has been developed so that position estimation can be performed in real time, and the performance is evaluated by performing three-dimensional localization with eight receiving antennas.

Fifth-generation mobile communication systems (5G) must offer significantly higher system capacity than 4G in order to accommodate the rapidly increasing mobile data traffic. Cell densification has been considered an effective way to increase system capacity. Unfortunately, each user equipment (UE) will be in line-of-sight to many more transmission points (TPs) and the resulting inter-cell interference will degrade system capacity. We propose large-scale coordinated multi-user multiple-input multiple-output (LSC-MU-MIMO), which combines MU-MIMO with joint transmission from all the TPs connected to a centralized baseband unit. We previously investigated the downlink performance of LSC-MU-MIMO by computer simulation and found that it can significantly reduce inter-TP interference and improve the system capacity of high-density small cells. In this paper, we investigate the throughput of LSC-MU-MIMO through an indoor trial where the number of coordinated TPs is up to sixteen by using an experimental system that can execute real-time channel estimation based on TDD reciprocity and real-time data transmission. To clarify the improvement in the system capacity of LSC-MU-MIMO, we compared the throughput measured in the same experimental area with and without coordinated transmission in 4-TP, 8-TP, and 16-TP configurations. The results show that with coordinated transmission the system capacity is almost directly proportional to the number of TPs.

The number of Internet-of-Things (IoT) devices will increase rapidly. In next-generation mobile communication systems, a base station (BS) must effectively accommodate massive numbers of IoT devices. To address this problem, we have proposed a novel up-link non-orthogonal multiple access (NOMA) system that can also be utilized for low latency communication. We have developed and evaluated the system through computer simulation. This paper describes experiments conducted on a prototype system in actual environments. The paper shows results of the experiments when 3 fixed user equipments (UEs) and 2 mobile UEs transmitted signals simultaneously to a BS and then the BS separated superimposed signals using successive interference cancellation (SIC). We also evaluated repetition transmission (RT) and space receive diversity (SD) techniques employed to enhance the signal separation performance for NOMA systems. The results of the experiments confirm that the system using neither SD nor RT could separate 3.5 UEs' signals on average while employing either SD or RT could make the number increase to 4.1 and 4.0, respectively. When both SD and RT were employed, the number rose to 4.4.

Denser infrastructures can reduce terminal-to-infrastructure distance and thus improve the link budget in mobile communication systems. One such infrastructure, relaying can reduce the distance between the donor evolved node B (eNB) and user equipment (UE). However, conventional relaying suffers from geographical constraints, i.e., installation site, and difficulty in simultaneous transmission and reception on the same carrier frequency. Therefore, we propose a new type of fiber-optic relaying in which the antenna facing the eNB is geographically separated from the antenna facing the UE, and the two antennas are connected by an optical fiber. This structure aims to extend coverage to heavily shadowed areas. Our primary objective is to establish a design method for the proposed fiber-optic relaying in the presence of self-interference, which is the interference between the backhaul and access links, when the backhaul and access links simultaneously operate on the same carrier frequency. In this paper, we present the performance of the fiber-optic relaying in the presence of intra- and inter-cell interferences as well as self-interference. The theoretical desired-to-undesired-signal ratio for both uplink and downlink is investigated as parameters of the optical fiber length. We demonstrate the possibility of fiber-optic relaying with simultaneous transmission and reception on the same carrier frequency for the backhaul and access links. We validate the design method for the proposed fiber-optic relay system using these results.

We present an OpenACC-based parallelization implementation of stochastic algorithms for simulating biochemical reaction networks on modern GPUs (graphics processing units). To investigate the effectiveness of using OpenACC for leveraging the massive hardware parallelism of the GPU architecture, we carefully apply OpenACC's language constructs and mechanisms to implementing a parallel version of stochastic simulation algorithms on the GPU. Using our OpenACC implementation in comparison to both the NVidia CUDA and the CPU-based implementations, we report our initial experiences on OpenACC's performance and programming productivity in the context of GPU-accelerated scientific computing.

In this work, we investigate a joint transmit beamforming and artificial noise (AN) covariance matrix design in a multiple-input multiple-output (MIMO) cognitive radio (CR) downlink network with simultaneous wireless information and power transfer (SWIPT), where the malicious energy receivers (ERs) may decode the desired information and hence can be treated as potential eavesdroppers (Eves). In order to improve the secure performance of the transmission, AN is embedded to the information-bearing signal, which acts as interference to the Eves and provides energy to all receivers. Specifically, this joint design is studied under a practical non-linear energy harvesting (EH) model, our aim is to maximize the secrecy rate at the SR subject to the transmit power budget, EH constraints and quality of service (QoS) requirement. The original problem is not convex and challenging to be solved. To circumvent its intractability, an equivalent reformulation of this secrecy rate maximization (SRM) problem is introduced, wherein the resulting problem is primal decomposable and thus can be handled by alternately solving two convex subproblems. Finally, numerical results are presented to verify the effectiveness of our proposed scheme.

This paper describes the results of outdoor mobility measurements and high-speed vehicle tests that clarify the 4-by-8 multiple-input multiple-output (MIMO) throughput performance when applying distributed MIMO with narrow antenna-beam tracking in a 28-GHz frequency band in the downlink of a 5G cellular radio access system. To clarify suitable transmission point (TP) deployment for mobile stations (MS) moving at high speed, we examine two arrangements for 3TPs. The first sets all TPs in a line along the same side of the path traversed by the MS, and the other sets one TP on the other side of the path. The experiments in which the MS is installed on a moving wagon reveal that the latter deployment case enables a high peak data rate and high average throughput performance exhibiting the peak throughput of 15Gbps at the vehicle speed of 3km/h. Setting the MS in a vehicle travelling at 30km/h yielded the peak throughput of 13Gbps. The peak throughput of 11Gbps is achieved at the vehicle speed of 100km/h, and beam tracking and intra-baseband unit hand over operation are successfully demonstrated even at this high vehicle speed.

In-phase and quadrature-phase imbalance (IQI) at transceivers is one of the serious hardware impairments degrading system performance. In this paper, we study the overall performance of massive multi-user multi-input multi-output (MU-MIMO) systems with IQI at both the base station (BS) and user equipments (UEs), including the estimation of channel state information, required at the BS for the precoding design. We also adopt a widely-linear precoding based on the real-valued channel model to make better use of the image components of the received signal created by IQI. Of particular importance, we propose estimators of the real-valued channel and derive the closed-form expression of the achievable downlink rate. Both the analytical and simulation results show that IQI at the UEs limits the dowlink rate to finite ceilings even when an infinite number of BS antennas is available, and the results also prove that the widely-linear precoding based on the proposed channel estimation method can improve the overall performance of massive MU-MIMO systems with IQI.

This paper introduces an energy-efficient transmit design for multiple-input single-output (MISO) energy-harvesting cognitive radio (CR) networks in the presence of external eavesdroppers (Eves). Due to the inherent characteristics of CR network with simultaneous wireless information and power transfer (SWIPT), Eves may illegitimately access the primary user (PU) bands, and the confidential message is prone to be intercepted in wireless communications. Assuming the channel state information (CSI) of the Eves is not perfectly known at the transmitter, our approach to guaranteeing secrecy is to maximize the secrecy energy efficiency (SEE) by jointly designing the robust beamforming and the power splitting (PS) ratio, under the constraints of total transmit power, harvested energy at secondary receiver (SR) and quality of service (QoS) requirement. Specifically, a non-linear energy harvesting (EH) model is adopted for the SR, which can accurately characterize the property of practical RF-EH circuits. To solve the formulated non-convex problem, we first employ fractional programming theory and penalty function to recast it as an easy-to-handle parametric problem, and then deal with the non-convexity by applying S-Procedure and constrained concave convex procedure (CCCP), which enables us to exploit the difference of concave functions (DC) programming to seek the maximum worst-case SEE. Finally, numerical results are presented to verify the performance of the proposed scheme.

This paper describes transmission line couplers for non-contact connecters. Their characteristics are formulated in closed forms and design methodologies are presented. As their applications, three different types of transmission line couplers, two-fold transmission line coupler, single-ended to differential conversion transmission line coupler, and rotatable transmission line coupler are reviewed.

Due to progressing process technology, yield of chips is reduced by timing violation caused by delay variation of gates and wires in fabrication. Recently, post-silicon delay tuning, which inserts programmable delay elements (PDEs) into clock trees before the fabrication and adjusts the delays of the PDEs to recover the timing violation after the fabrication, is promising to improve the yield. Although post-silicon delay tuning improves the yield, it increases circuit area and power consumption since the PDEs are inserted. In this paper, a PDE structure is taken into consideration to reduce the circuit area and the power consumption. Moreover, a delay selection algorithm, and a clustering method, in which some PDEs are merged into a PDE and the PDE is inserted for multiple registers, are proposed to reduce the circuit area and the power consumption. In computational experiments, the proposed method reduced the circuit area and the power consumption in comparison with an existing method.

This paper discusses the impact of stacking on-chip inductor on power/ground network. Stacking inductor on other circuit components can reduce the circuit area drastically, however, the impact on signal and power integrity is not clear. We investigate the impact by a field-solver, a circuit simulator and real chip measurement. We evaluate three types of power/ground network and various multi-layered inductors. Experimental results show that dense power/ground structures reduce noise although the coupling capacitance becomes larger than that of sparse structures. Measurement in a 65-nm CMOS shows a woven structure makes the noise voltage half compared to a sparse structure.

This paper presents a low-power small-area-overhead physical random number generator utilizing SAR ADC embedded in sensor SoCs. An unpredictable random bit sequence is produced by an existing comparator in typical SAR ADCs, which results in little area overhead. Unlike the other comparator-based physical random number generator, this proposed technique does not require an offset calibration scheme since SAR binary search algorithm automatically converges the two input voltages of the comparator to balance the differential circuit pair. Although the randomness slightly depends on an quantization error due to sharing AD conversion scheme, the input signal distribution enhances the quality of random number bit sequence which can use for various security countermeasures such as masking techniques. Fabricated in 180nm CMOS, 1Mb/s random bit generator achieves high efficiency of 0.72pJ/bit with only 400μm2 area overhead, which occupies less than 0.5% of SAR ADC, while remaining 10-bit AD conversion function.

With advances in information technology and the development of big data, manual operation is unlikely to be a smart choice for stock market investing. Instead, the computer-based investment model is expected to bring investors more accurate strategic analysis and more effective investment decisions than human beings. This paper aims to improve investor profits by mining for critical information in the stock data, therefore helping big data analysis. We used the R language to find the technical indicators in the stock market, and then applied the technical indicators to the prediction. The proposed R package includes several analysis toolkits, such as trend line indicators, W type reversal patterns, V type reversal patterns, and the bull or bear market. The simulation results suggest that the developed R package can accurately present the tendency of the price and enhance the return on investment.

In this research, we propose a novel method to determine fingerprint liveness to improve the discriminative behavior and classification accuracy of the combined features. This approach detects if a fingerprint is from a live or fake source. In this approach, fingerprint images are analyzed in the differential excitation (DE) component and the centralized binary pattern (CBP) component, which yield the DE image and CBP image, respectively. The images obtained are used to generate a two-dimensional histogram that is subsequently used as a feature vector. To decide if a fingerprint image is from a live or fake source, the feature vector is processed using support vector machine (SVM) classifiers. To evaluate the performance of the proposed method and compare it to existing approaches, we conducted experiments using the datasets from the 2011 and 2015 Liveness Detection Competition (LivDet), collected from four sensors. The results show that the proposed method gave comparable or even better results and further prove that methods derived from combination of features provide a better performance than existing methods.

Temporal behavior is a primary aspect of business process executions. Herein, we propose a temporal outlier detection and analysis method for business processes. Particularly, the method performs correlation analysis between the execution times of traces and activities to determine the type of activities that significantly influences the anomalous temporal behavior of a trace. To this end, we describe the modeling of temporal behaviors considering different control-flow patterns of business processes. Further, an execution time matrix with execution times of activities in all traces is constructed by using the event logs. Based on this matrix, we perform temporal outlier detection and correlation-based analysis.

This paper presents a conifer and broad-leaf tree classification scheme that processes high resolution polarimetric synthetic aperture data above X-band. To validate the proposal, fully polarimetric measurements are conducted in a precisely controlled environment to examine the difference between the scattering mechanisms of conifer and broad-leaf trees at 15GHz. With 3.75cm range resolution, scattering matrices of two tree types were measured by a vector network analyzer. Polarimetric analyses using the 4-component scattering power decomposition and alpha-bar angle of eigenvalue decomposition yielded clear distinction between the two tree types. This scheme was also applied to an X-band Pi-SAR2 data set. The results confirm that it is possible to distinguish between tree types using fully polarimetric and high-resolution data above X-band.

The compressive sensing has been applied to develop an effective framework for simultaneously localizing multiple targets in wireless sensor networks. Nevertheless, existing methods implicitly use analog measurements, which have infinite bit precision. In this letter, we focus on off-grid target localization using quantized measurements with only several bits. To address this, we propose a novel localization framework for jointly estimating target locations and dealing with quantization errors, based on the novel application of the variational Bayesian Expectation-Maximization methodology. Simulation results highlight its superior performance.

Currently, visual perceptions generated by visual prosthesis are low resolution with unruly color and restricted grayscale. This severely restricts the ability of prosthetic implant to complete visual tasks in daily scenes. Some studies explore existing image processing techniques to improve the percepts of objects in prosthetic vision. However, most of them extract the moving objects and optimize the visual percepts in general dynamic scenes. The application of visual prosthesis in daily life scenes with high dynamic is greatly limited. Hence, in this study, a novel unsupervised moving object segmentation model is proposed to automatically extract the moving objects in high dynamic scene. In this model, foreground cues with spatiotemporal edge features and background cues with boundary-prior are exploited, the moving object proximity map are generated in dynamic scene according to the manifold ranking function. Moreover, the foreground and background cues are ranked simultaneously, and the moving objects are extracted by the two ranking maps integration. The evaluation experiment indicates that the proposed method can uniformly highlight the moving object and keep good boundaries in high dynamic scene with other methods. Based on this model, two optimization strategies are proposed to improve the perception of moving objects under simulated prosthetic vision. Experimental results demonstrate that the introduction of optimization strategies based on the moving object segmentation model can efficiently segment and enhance moving objects in high dynamic scene, and significantly improve the recognition performance of moving objects for the blind.

A programmable analog calculation unit (ACU) is designed for vector computations in continuous-time with compact circuit scale. From our early study, it is feasible to retrieve arbitrary two-variable functions through support vector regression (SVR) in silicon. In this work, the dimensions of regression are expanded for vector computations. However, the hardware cost and computing error greatly increase along with the expansion of dimensions. A two-stage architecture is proposed to organize multiple ACUs for high dimensional regression. The computation of high dimensional vectors is separated into several computations of lower dimensional vectors, which are implemented by the free combination of several ACUs with lower cost. In this manner, the circuit scale and regression error are reduced. The proof-of-concept ACU is designed and simulated in a 0.18μm technology. From the circuit simulation results, all the demonstrated calculations with nine operands are executed without iterative clock cycles by 4960 transistors. The calculation error of example functions is below 8.7%.