Chipless tag systems composed of multimode stepped impedance resonators (SIRs) and a reader based on near-field electromagnetic coupling have been reported. This resonator structure has advantages including a simple design due to its symmetrical structure and good discrimination accuracy because many higher-order mode resonant frequencies can be used for identification of codes. However, in addition to the disadvantage of long resonator length, the frequency response in the tag system becomes unstable due to deterioration of the isolation between the probes because the same probe structure is used for the excitor and detector. In this paper, we propose two methods to solve these problems. One is to adopt an asymmetrical SIR structure with a short-circuited end and open-circuited end, which reduces the resonator length by half while allowing the same number of codes to be generated. The other is to improve isolation between probes by applying different magnetic field and electric field structures to the two probes for excitation and detection. We also examined assignment and identification conditions and clarified that the available number of codes for a unit tag can be more than 15 bits. It becomes clear that a 75-bit chipless tag on a credit card-sized (55×86mm) printed circuit board can be designed by integrating five unit tags.

In IoT (Internet-of-Things) era, the number and variety of hardware devices becomes continuously increasing. Several IoT devices are utilized at infrastructure equipments. How to maintain such IoT devices is a serious concern. Capacitance measurement is one of the powerful ways to detect anomalous states in the structure of the hardware devices. Particularly, measuring capacitance while the hardware device is running is a major challenge but no such researches proposed so far. This paper proposes a capacitance measuring device which measures device capacitance in operation. We firstly combine the AC (alternating current) voltage signal with the DC (direct current) supply voltage signal and generates the fluctuating signal. We supply the fluctuating signal to the target device instead of supplying the DC supply voltage. By effectively filtering the observed current in the target device, the filtered current can be proportional to the capacitance value and thus we can measure the target device capacitance even when it is running. We have implemented the proposed capacitance measuring device on the printed wiring board with the size of 95mm × 70mm and evaluated power consumption and accuracy of the capacitance measurement. The experimental results demonstrate that power consumption of the proposed capacitance measuring device is reduced by 65% in low-power mode from measuring mode and proposed device successfully measured capacitance in 0.002μF resolution.

Analyzing aging-induced delay degradations of ring oscillators (ROs) is an effective way to detect recycled field-programmable gate arrays (FPGAs). However, it requires a large number of RO measurements for all FPGAs before shipping, which increases the measurement costs. We propose a cost-efficient recycled FPGA detection method using a statistical performance characterization technique called virtual probe (VP) based on compressed sensing. The VP technique enables the accurate prediction of the spatial process variation of RO frequencies on a die by using a very small number of sample RO measurements. Using the predicted frequency variation as a supervisor, the machine-learning model classifies target FPGAs as either recycled or fresh. Through experiments conducted using 50 commercial FPGAs, we demonstrate that the proposed method achieves 90% cost reduction for RO measurements while preserving the detection accuracy. Furthermore, a one-class support vector machine algorithm was used to classify target FPGAs with around 94% detection accuracy.

To solve the area and power problems in Finite Impulse Response (FIR) implementations, a faithfully truncated adder-based FIR design is presented in this paper for significant area and power savings while the predefined output accuracy can still be obtained. As a solution to the accuracy loss caused by truncated adders, a static error analysis on the utilization of truncated adders in FIRs was performed. According to the mathematical analysis, we show that, with a given accuracy constraint, the optimal truncated adder configuration for an area-power efficient FIR design can be effortlessly determined. Evaluation results on various FIR implementations by using the proposed faithfully truncated adder designs showed that up to 35.4% and 27.9% savings in area and power consumption can be achieved with less than 1 ulp accuracy loss for uniformly distributed random inputs. Moreover, as a case study for normally distributed signals, a fixed 6-tap FIR is implemented for electrocardiogram (ECG) signal filtering was implemented, in which even with the increased truncated bits up to 10, the mean absolute error (Ē) can be guaranteed to be less than 1 ulp while up to 29.7% and 25.3% savings in area and power can be obtained.

The paper deals with the shortest path-based in-trees on a grid graph. There a root is supposed to move among all vertices. As such a spanning mobility pattern, root trajectories based on a Hamilton path or cycle are discussed. Along such a trajectory, each vertex randomly selects the next hop on the shortest path to the root. Under those assumptions, this paper shows that a root trajectory termed an S-path provides the minimum expected symmetric difference. Numerical experiments show that another trajectory termed a Right-cycle also provides the minimum result.

A method of determining emission limits was studied by using the amplitude probability distribution (APD) for low-probability pulsed electromagnetic disturbances due to discharge. The features of this method are 1) without using the previously reported relationship between APD and bit error rate, the limits are derived using the measured impact of a pulsed disturbance on various wireless communication systems having different bandwidths, and 2) disturbances caused by discharge with poor reproducibility are simulated by regularly repeated pulse-modulated sine waves to enable stable evaluation of the communication quality. APD-based limits are determined from the pulse repetition frequency of the simulated disturbance such that the block error rate (BLER) is less than a certain limit in wireless systems that are most sensitive to the pulsed disturbance. In the international standard CISPR 32 regulating electromagnetic disturbance, radiated disturbance due to discharge is excluded from the application of peak detection limits because of its low occurrence probability. In this paper we quantitatively determine appropriate criteria of the probability for the exclusion. Using the method, we measured the impact of low-probability pulsed interference on major wireless systems and found that GSM and Wi-Fi systems were the most sensitive. New APD-based limits were derived on the basis of these findings. The APD-based limits determined by the proposed method enable a valid evaluation of low-occurrence-probability pulsed disturbances without unconditionally excluding the measurement.

This paper presents a comparative loss analysis performed between an LLC converter and a phase-shift converter under the same size conditions using a power supply manufactured for information communications equipment. It is also shown herein that the LLC converter has a much higher ratio of transformer loss to total loss than the phase-shift converter and that the cause is the difference in the number of transformer turns between the two converters. Further, the ON-resistance of the secondary-side rectifier element and the number of transformer primary turns are shown to determine which of the two converters is superior in terms of low loss.

Connecting a large number of servers with high bandwidth links is one of the most crucial and challenging tasks that the Data Center Network (DCN) must fulfill. DCN faces a lot of difficulties like the effective exploitation of DC components that, if highlighted, can aid in constructing high performance, scalable, reliable, and cost-effective DCN. In this paper, we investigate the server-centric structure. We observe that current DCs use servers that mostly come with dual ports. Effective exploitation of the ports of interest for building the topology structure can help in realizing the potentialities of reducing expensive topology. Our new network topology, named “Parallel Cubes” (PCube), is a duplicate defined structure that utilizes the ports in the servers and mini-switches to form a highly effective, scalable, and efficient network structure. P-Cube provides high performance in network latency and throughput and fault tolerance. Additionally, P-Cube is highly scalable to encompass hundreds of thousands of servers with a low stable diameter and high bisection width. We design a routing algorithm for P-Cube network that utilizes the P-Cube structure to strike a balance among the numerous links in the network. Finally, numerical results are provided to show that our proposed topology is a promising structure as it outperforms other topologies and it is superior to Fat-tree, BCube and DCell by approximately 24%, 16%, 8% respectively in terms of network throughput and latency. Moreover, P-Cube extremely outperforms Fat-tree, and BCube structures in terms of total cost, complexity of cabling and power consumption.

This paper proposes a computational complexity-reduced algorithm for an adaptive peak-to-average power ratio (PAPR) reduction method previously developed by members of our research group that uses the null space in a multiple-input multiple-output (MIMO) channel for MIMO-orthogonal frequency division multiplexing (OFDM) signals. The proposed algorithm is an extension of the peak cancellation (PC) signal-based method that has been mainly investigated for per-antenna PAPR reduction. This method adds the PC signal, which is designed so that the out-of-band radiation is removed/reduced, directly to the time-domain transmission signal at each antenna. The proposed method, referred to as PCCNC (PC with channel-null constraint), performs vector-level signal processing in the PC signal generation so that the PC signal is transmitted only to the null space in the MIMO channel. We investigate three methods to control the beamforming (BF) vector in the PC signal, which is a key factor in determining the achievable PAPR performance of the algorithm. Computer simulation results show that the proposed PCCNC achieves approximately the same throughput-vs.-PAPR performance as the previous method while dramatically reducing the required computational cost.

Green cognitive radio (CR) plays an important role in offering secondary users (SUs) with more spectrum with smaller energy expenditure. However, the energy efficiency (EE) issues associated with green CR for fading channels have not been fully studied. In this paper, we investigate the average EE maximization problem for spectrum-sharing CR in fading channels. Unlike previous studies that considered either the peak or the average transmission power constraints, herein, we considered both of these constraints. Our aim is to maximize the average EE of SU by optimizing the transmission power under the joint peak and average transmit power constraints, the rate constraint of SU and the quality of service (QoS) constraint of primary user (PU). Specifically, the QoS for PU is guaranteed based on either the average interference power constraint or the PU outage constraint. To address the non-convex optimization problem, an iterative optimal power allocation algorithm that can tackle the problem efficiently is proposed. The optimal transmission powers are identified under both of perfect and imperfect channel side information (CSI). Simulations show that our proposed scheme can achieve higher EE over the existing scheme and the EE achieved under perfect CSI is better than that under imperfect CSI.

Synthetic aperture interferometric radiometer (SAIR) is a powerful sensors for high-resolution imaging. However, because of the observation errors and small number of visibility sampling points, the accuracy of reconstructed images is usually low. To overcome this deficiency, a novel super-resolution imaging (SrI) method based on super-resolution reconstruction idea is proposed in this paper. In SrI method, sparse visibility functions are first measured at different observation locations. Then the sparse visibility functions are utilized to simultaneously construct the fusion visibility function and the fusion imaging model. Finally, the high-resolution image is reconstructed by solving the sparse optimization of fusion imaging model. The simulation results demonstrate that the proposed SrI method has higher reconstruction accuracy and can improve the imaging quality of SAIR effectively.

Matching circuits using LC elements are widely applied to high-frequency circuits such as power amplifier (PA) and low-noise amplifier (LNA). For determining matching condition of multi-stage matching circuits, this paper shows that any multi-stage LC-Ladder matching circuit with resistive termination can be decomposed to the extended L-type matching circuits with resistive termination containing negative elements where the analytical solution exists. The matching conditions of each extended L-type matching circuit are obtained easily from the termination resistances and the design frequency. By synthesizing these simple analysis solutions, it is possible to systematically determine the solution even in a large number of stages (high order) matching circuits.

In this paper, we study a radio frequency (RF)-powered backscatter assisted cognitive radio network (CRN), where an eavesdropper exists. This network includes a primary transmitter, a pair of secondary transmitter and receiver, a friendly jammer and an eavesdropper. We assume that the secondary transmitter works in ambient backscatter (AmBack) mode and the friendly jammer works in harvest-then-transmit (HTT) mode, where the primary transmitter serves as energy source. To enhance the physical layer security of the secondary user, the friendly jammer uses its harvested energy from the primary transmitter to transmit jamming noise to the eavesdropper. Furthermore, for maximizing the secrecy rate of secondary user, the optimal time allocation including the energy harvesting and jamming noise transmission phases is obtained. Simulation results verify the superiority of the proposed scheme.

A planar electromagnetic field stirrer with periodically arranged metal patterns and diode switches is proposed for improving uneven heating of a heated object placed in a microwave oven. The reflection phase of the proposed stirrer changes by switching the states of diodes mounted on the stirrer and the electromagnetic field in the microwave oven is stirred. The temperature distribution of a heated object located in a microwave oven was simulated and measured using the stirrer in order to evaluate the improving effect of the uneven heating. As the result, the heated parts of the objects were changed with the diode states and the improving effect of the uneven heating was experimentally indicated.

In wireless sensor networks (WSN), communication interference and the energy limitation of sensor nodes seriously hamper the network performance such as throughput and network lifetime. In this paper, we focus on the Successive Interference Cancellation (SIC) and Wireless Energy Transmission (WET) technology aiming to design a heuristic power control algorithm and an efficient cross-layer strategy to realize concurrency communication and improve the network throughput, channel utilization ratio and network lifetime. We realize that the challenge of this problem is that joint consideration of communication interference and energy shortage makes the problem model more complicated. To solve the problem efficiently, we adopt link scheduling strategy, time-slice scheduling scheme and energy consumption optimization protocol to construct a cross-layer optimization problem, then use an approximate linearization method to transform it into a linear problem which yields identical optimal value and solve it to obtain the optimal work strategy of wireless charging equipment (WCE). Simulation results show that adopting SIC and WCE can greatly improve communication capability and channel utilization ratio, and increase throughput by 200% to 500% while prolonging the network lifetime.

A limited number of types of sound event occur in an acoustic scene and some sound events tend to co-occur in the scene; for example, the sound events “dishes” and “glass jingling” are likely to co-occur in the acoustic scene “cooking.” In this paper, we propose a method of sound event detection using graph Laplacian regularization with sound event co-occurrence taken into account. In the proposed method, the occurrences of sound events are expressed as a graph whose nodes indicate the frequencies of event occurrence and whose edges indicate the sound event co-occurrences. This graph representation is then utilized for the model training of sound event detection, which is optimized under an objective function with a regularization term considering the graph structure of sound event occurrence and co-occurrence. Evaluation experiments using the TUT Sound Events 2016 and 2017 detasets, and the TUT Acoustic Scenes 2016 dataset show that the proposed method improves the performance of sound event detection by 7.9 percentage points compared with the conventional CNN-BiGRU-based detection method in terms of the segment-based F1 score. In particular, the experimental results indicate that the proposed method enables the detection of co-occurring sound events more accurately than the conventional method.

Some non-acoustic modalities have the ability to reveal certain speech attributes that can be used for synthesizing speech signals without acoustic signals. This study validated the use of ultrasonic Doppler frequency shifts caused by facial movements to implement a silent speech interface system. A 40kHz ultrasonic beam is incident to a speaker's mouth region. The features derived from the demodulated received signals were used to estimate the speech parameters. A nonlinear regression approach was employed in this estimation where the relationship between ultrasonic features and corresponding speech is represented by deep neural networks (DNN). In this study, we investigated the discrepancies between the ultrasonic signals of audible and silent speech to validate the possibility for totally silent communication. Since reference speech signals are not available in silently mouthed ultrasonic signals, a nearest-neighbor search and alignment method was proposed, wherein alignment was achieved by determining the optimal pair of ultrasonic and audible features in the sense of a minimum mean square error criterion. The experimental results showed that the performance of the ultrasonic Doppler-based method was superior to that of EMG-based speech estimation, and was comparable to an image-based method.

In IoT systems, data acquired by many sensors are required. However, since sensor operation depends on the actual environment, it is important to ensure sensor redundancy to improve system reliability in IoT systems. To evaluate the safety of the system, it is important to estimate the achievement probability of the function based on the sensing probability. In this research, we proposed a method to automatically generate a PRISM model from the sensor configuration of the target system and calculate and verify the function achievement probability in the assumed environment. By designing and evaluating iteratively until the target achievement probability is reached, the reliability of the system can be estimated at the initial design phase. This method reduces the possibility that the lack of reliability will be found after implementation and the redesign accompanying it will occur.

The accurate calculation of the inductance is the most basic problem of the inductor design. In this paper, the core flux density distribution and leakage flux in core window and winding of core-type inductor are analyzed by finite element analysis (FEA) firstly. Based on it, an improved magnetic equivalent circuit with high accuracy flux density distribution (iMEC) is proposed for a single-phase core-type inductor. Depend on the geometric structure, two leakage paths of the core window are modeled. Furthermore, the iMEC divides the magnetomotive force of the winding into the corresponding core branch. It makes the core flux density distribution consistent with the FEA distribution to improve the accuracy of the inductance. In the iMEC, flux density of the core leg has an error less than 5.6% compared to FEA simulation at 150A. The maximum relative error of the inductance is less than 8.5% and the average relative error is less than 6% compared to the physical prototype test data. At the same time, due to the high computational efficiency of iMEC, it is very suitable for the population-based optimization design.

This paper describes graph-based Wave Function Collapse algorithm for procedural content generation. The goal of this system is to enable a game designer to procedurally create key content elements in the game level through simple association rule input. To do this, we propose a graph-based data structure that can be easily integrated with a navigation mesh data structure in a three-dimensional world. With our system, if the user inputs the minimum association rule, it is possible to effectively perform procedural content generation in the three-dimensional world. The experimental results show that the Wave Function Collapse algorithm, which is a texture synthesis algorithm, can be extended to non-grid shape content with high controllability and scalability.