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 have already proposed synchronized spread spectrum code division multiple access (SS-CDMA) for the Quasi-Zenith Satellite System (QZSS) safety confirmation system to be used in times of great disaster. In this system, the satellite reception timings of all uplink signals are synchronized using a transmission timing control method in order to realize high-density user multiple access. An issue that should be addressed in order for this system to be viable is the error that can occur in the satellite reception timing. This error occurs due to the terminal time deviation and the error in calculating the propagation delay to the satellite. In this paper, we measure the terminal time deviation and the propagation delay calculation error at the same time by using the same receivers and evaluate the satellite reception timing error of the uplink signal. By this measurement, it is shown that satellite reception timing error within 50ns can be realized in 99.98% of mobile terminals. This shows that the synchronized SS-CDMA with the transmission timing control method has a potential to realize the QZSS short message system with high-density user multiple access.

This paper proposes a path loss model for crowded outdoor environments that can consider the density of people. Measurement results in an anechoic chamber with three blocking persons showed that multiple human body shadowing can be calculated by using finite width screens. As a result, path loss in crowded environments can be calculated by using the path losses of the multipath and the multiple human body shadowing on those paths. The path losses of the multipath are derived from a ray tracing simulation, and the simulation results are then used to predict the path loss in crowded environments. The predicted path loss of the proposed model was examined through measurements in the crowded outdoor station square in front of Shibuya Station in Tokyo, and results showed that it can accurately predict the path loss in crowded environments at the frequencies of 4.7GHz and 26.4GHz under two different conditions of antenna height and density of people. The RMS error of the proposed model was less than 4dB.

Symbolic execution is capable of automatically generating tests that achieve high coverage. However, its practical use is limited by the scalability problem. To mitigate it, this paper proposes State Concretization based Symbolic Execution (SCSE). SCSE speeds up symbolic execution via state concretization. Specifically, by introducing a concrete store, our approach avoids invoking the constraint solver to check path feasibility at conditional instructions. Intuitively, there is no need to check the feasibility of a path along a concrete execution since it is always feasible. With state concretization, the number of solver queries greatly decreases, thus improving the efficiency of symbolic execution. Through experimental evaluation on real programs, we show that state concretization helps to speed up symbolic execution significantly.

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 LTE (Long Term Evolution) / LTE-Advanced (LTE-A) system, the user-plane for a user equipment (UE) is provided by tunneling, which increases header overhead, processing overhead, and management overhead. In addition, the LTE-A system does not support moving cells which are composed of a mobile Relay Node (RN) and UEs attached to the mobile RN. Although there are several proposals for moving cells in the LTE-A system and the 5G system, all of them rely on tunneling for the user-plane, which means that none of them avoid the tunneling overheads. This paper proposes MocLis, a moving cell support protocol based on a Locator/ID split approach. MocLis does not use tunneling. Nested moving cells are supported. Signaling cost for handover of a moving cell is independent of the number of UEs and nested RNs in the moving cell. A MocLis prototype, implemented in Linux, includes user space daemons and modified kernel. Measurements show that the attachment time and handover time are short enough for practical use. MocLis has higher TCP throughput than the tunneling based approaches.

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.

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.

An efficient resistive random access memory (ReRAM) structure is developed for accelerating convolutional neural network (CNN) powered by the in-memory computation. A novel ReRAM cell circuit is designed with two-directional (2-D) accessibility. The entire memory system is organized as a 2-D array, in which specific memory cells can be identically accessed by both of column- and row-locality. For the in-memory computations of CNNs, only relevant cells in an identical sub-array are accessed by 2-D read-out operations, which is hardly implemented by conventional ReRAM cells. In this manner, the redundant access (column or row) of the conventional ReRAM structures is prevented to eliminated the unnecessary data movement when CNNs are processed in-memory. From the simulation results, the energy and bandwidth efficiency of the proposed memory structure are 1.4x and 5x of a state-of-the-art ReRAM architecture, respectively.

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.

In this paper, a high-frequency resolution Digital Frequency Discriminator (DFD) IC using a Time to Digital Converter (TDC) and an edge counter for Instantaneous Frequency Measurement (IFM) is proposed. In the proposed DFD, the TDC measures the time of the maximum periods of divided RF short pulse signals, and the edge counter counts the maximum number of periods of the signal. By measuring the multiple periods with the TDC and the edge counter, the proposed DFD improves the frequency resolution compared with that of the measuring one period because it is proportional to reciprocal of the measurement time of TDC. The DFD was fabricated using 0.18-um SiGe-BiCMOS. Frequency accuracy below 0.39MHz and frequency precision below 1.58 MHz-RMS were achieved during 50 ns detection time in 0.3 GHz to 5.5 GHz band with the temperature range from -40 to 85 degrees.

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.

A concurrent system consists of multiple processes that are run simultaneously. The execution orders of these processes are defined by a scheduler. In model checking techniques, the scheduling policy is closely related to the search algorithm that explores all of the system states. To ensure the correctness of the system, the scheduling policy needs to be taken into account during the verification. Current approaches, which use fixed strategies, are only capable of limited kinds of policies and are difficult to extend to handle the variations of the schedulers. To address these problems, we propose a method using a domain-specific language (DSL) for the succinct specification of different scheduling policies. Necessary artifacts are automatically generated from the specification to analyze the behaviors of the system. We also propose a search algorithm for exploring the state space. Based on this method, we develop a tool to verify the system with the scheduler. Our experiments show that we could serve the variations of the schedulers easily and verify the systems accurately.

This new design uses a low power embedded controller (EC) in cooperation with the BIOS of a notebook (NB) computer, both to accomplish dynamic adjustment and to maintain a required performance level of the battery mode of the notebook. In order to extend the operation time at the battery mode, in general, the notebook computer will directly reduce the clock rate and then reduce the performance. This design can obtain the necessary balance of the performance and the power consumption by using both the EC and the BIOS cooperatively to implement the dynamic control of both the CPU and the GPU frequency to maintain the system performance at a sufficient level for a high speed and high resolution video game. In contrast, in order to maintain a certain notebook performance, in terms of battery life it will be necessary to make some trade-offs.

The real-time state-of-health (SOH) estimation of lithium-ion batteries for electric vehicles (EV) is essential to EV maintenance. According to situations in practical applications such as long EV battery capacity test time, unavailability of regular daily tests, and availability of full-life-cycle charge data of EV recorded on the charging facility big data platform, this paper studies an online in-use EV state-of-health estimation method using iterated extended Gaussian process regression-Kalman filter (GPR-EKF) to incorporate lithium-ion battery data at the macro time scale and the micro time scale based on daily charge data of electric vehicles. This method proposes a kernel function GPR (Gaussian process regression) integrating neutral network with cycles to conduct fitting for data at the macro time scale to determine colored measurement noise; in addition, fragment charge data at the micro time scale is adjusted with real-time iteration to be used as the state equation, which effectively addresses issues of real-time SOC calibration and nonlinearization. The pertinence, effectiveness and real-time performance of the model algorithm in online battery state-of-health estimation is verified by actual data.

The 3D holographic display has long been expected as a future human interface as it does not require users to wear special devices. However, its heavy computation requirement prevents the realization of such displays. A recent study says that objects and holograms with several giga-pixels should be processed in real time for the realization of high resolution and wide view angle. To this problem, first, we have adapted a conventional FFT algorithm to a GPU cluster environment in order to avoid heavy inter-node communications. Then, we have applied several single-node and multi-node optimization and parallelization techniques. The single-node optimizations include a change of the way of object decomposition, reduction of data transfer between the CPU and GPU, kernel integration, stream processing, and utilization of multiple GPUs within a node. The multi-node optimizations include distribution methods of object data from host node to the other nodes. Experimental results show that intra-node optimizations attain 11.52 times speed-up from the original single node code. Further, multi-node optimizations using 8 nodes, 2 GPUs per node, attain an execution time of 4.28 sec for generating a 1.6 giga-pixel hologram from a 3.2 giga-pixel object. It means a 237.92 times speed-up of the sequential processing by CPU and 41.78 times speed-up of multi-threaded execution on multicore-CPU, using a conventional FFT-based algorithm.

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.