This paper proposes the load-independent class-E Zero-Voltage Switching (ZVS) power oscillator. Conventional class-E power oscillator has a load-dependent phase shift, which hinders sustained oscillation under varying load conditions. Hence, we introduce the class-E power amplifier that ensures the load-independent phase shift in the output current. By incorporating it into an LCLC filter with a resonant-capacitor feedback network, the load-independent self-oscillation is realized. The proposed power oscillator satisfies a phase-shift requirement for sustained oscillation regardless of the load resistance. Furthermore, the proposed circuit exhibits load independence in ZVS, output current, and gate-drive voltage. This paper provides a thorough analysis of the proposed power oscillator, covering its operating principle, power loss prediction, design, and limitations. This paper also gives two design examples with 0.8 MHz and 6.78 MHz oscillation frequencies. In the experiment, the prototype power oscillators achieved 93.8 % and 87.4 % power-conversion efficiencies, respectively. The validity and effectiveness of the proposed power oscillator are demonstrated from the experimental verifications.

Edge computing brings computational resources to network edge, enabling mobile devices (MDs) to offload computing-intensive tasks to nearby edge servers. This significantly reduces the energy consumption of MDs and supports latency-sensitive applications. Meanwhile, the advancement of full-duplex (FD) cell-free massive multiple-input multiple-output (MIMO) technology provides a promising opportunity to enhance end-edge communication efficiency, particularly in scenarios with coexisting uplink (UL) and downlink (DL) users. In this paper, we investigate the joint task offloading and resource scheduling problem in FD cell-free massive MIMO-enabled edge computing networks. The problem is formulated as a two-stage optimization framework. In the first stage, we develop a hybrid simulated annealing–particle swarm optimization (SA-PSO) algorithm, which incorporates the Metropolis criterion to enhance global search capability, aiming to maximize spectral efficiency. In the second stage, we propose a diffusion-augmented prioritized deep deterministic policy gradient (DAP-DDPG) algorithm. This algorithm integrates prioritized experience replay with diffusion models to minimize the total energy consumption of MDs while satisfying stringent latency constraints. Simulation results demonstrate that, compared with benchmark schemes, the proposed SA-PSO algorithm achieves a 13.4% to 146% improvement in spectral efficiency, while the DAP-DDPG algorithm reduces the energy consumption of MDs by 12.5% to 33.1%.

The integration of the Internet of Things (IoT) with blockchain technology offers a promising solution to tackle interoperability, privacy, and security issues in IoT applications. However, maintaining low latency is a significant challenge in IoT-blockchain systems, as blockchain relies on an underlying communication network to create an overlay network for transmission and synchronization. The random nature of blockchain’s broadcast mechanism results in an overlay network topology that is not optimized for low-latency transmission. This study examines the impact of overlay network topologies on latency performance within an Ethereum-based IoT system. We developed a novel method for generating various overlay topology configurations and implemented Ethereum clients to establish neighboring connections based on these configurations. Our findings reveal that the overlay network significantly influences latency metrics, specifically the delays in transmitting transactions or blocks. We observed that the trade-off between delays caused by network congestion and latency reduction from fewer hops in the overlay network is dependent on the number of connections. To investigate further, we implemented three models for overlay networks. None of these network models consistently exhibited superior latency performance, indicating that latency is affected by network dynamics. In response, we developed an efficient peer selection method for blockchain nodes to reduce latency in dynamic environments. Drawing inspiration from the Perigee algorithm’s success in peer selection for transaction propagation, we propose Dual Perigee, an extension of Perigee that also optimizes block propagation latency. Through experiments in an emulated 50-node IoT-blockchain system, we compared the effectiveness of Dual Perigee against Ethereum’s default peering method and the Perigee algorithm. The results demonstrate that Dual Perigee reduces block latency by 48.5 %. These latency reductions enable more real-time responsiveness in IoT-blockchain systems and support their deployment in latency-sensitive applications.

Federated learning (FL) is a distributed machine learning (ML) paradigm designed for numerous networked devices. To face the massive data generated by devices and privacy concerns in model construction, the paradigm can execute ML tasks with differential privacy (DP) over private data streams. In each FL training iteration, a few clients are selected to participate and consume privacy budgets that determine the level of privacy protection. The client selection strategy plays a pivotal role in the final model performance. At present, reconciling model performance with privacy protection remains an open issue in online settings. Specifically, the DP model designed for data streams reduces the benefits of frequent participation by clients with high-quality data, as the DP model constrains the available privacy budget of continuous iterations. To address this issue, we propose a novel client selection framework for FL with DP-based data streams. At a macro level, we leverage fuzzy control to dynamically adjust the participation rate of clients, ensuring sufficient privacy budgets are allocated in each training iteration. At a fine-grained level, we design a dynamic scoring function based on the characteristics of the clients and a budget-aware client selection method to select clients further. Additionally, considering the diverse scenarios in data collection, we propose a relaxed semi-online setting and integrate reinforcement learning (RL) to enhance the framework performance. Extensive experiments demonstrate the remarkable advantages of our framework in accuracy, convergence rate, robustness, etc.

A hybrid wired/wireless SDN switch enables unified control across mixed-access networks but faces challenges in real-time traffic classification and flow management due to the lack of intelligence. This paper presents an intelligent hybrid SDN switch augmented with embedded machine learning (ML) models for accurate traffic classification and low-latency prediction. We evaluated six supervised ML algorithms, Logistic Regression, Random Forest, Support Vector Machine, Naive Bayes, k-Nearest Neighbors, and Neural Network, under both single-flow and concurrent multiflow scenarios using real traffic traces, including DNS, Ping, Telnet, and interactive gaming protocols. The evaluation results show that the Random Forest model consistently outperforms others, achieving classification accuracies of 99.97% in single-flow and 99.86% in multi-flow scenarios, while accurately predicting the traffic in millisecond-level inference latency. These findings demonstrate the feasibility of embedding ML-driven intelligence into hybrid SDN switches to support real-time, application-aware traffic control in emerging network infrastructures.

This paper proposes a machine learning (ML)–based design for a load-independent (LI) wireless power transfer (WPT) system. The fundamental concept of the proposed design strategy is to solve an optimization problem for achieving high-frequency LI operation by full numerical computations. An evaluation function for optimization is formulated, taking into account output voltage regulation against load variations and high power-delivery efficiency. The developed optimization software provides the best parameter set of coupling coil parameters and circuit-component values. In addition, the ML-based optimization finds the optimal parameter set from parameters outside the range that it had considered to be common sense, which is an unexpected but valuable result. The WPT system, designed through the proposed method, achieved ideal LI operation in the experiments. The quantitative agreements between experimental and numerical waveforms substantiate the validity of the proposed design.

In this paper, a WPT system that can switch between constant current (CC) and constant voltage (CV) in a single circuit is proposed. In the proposed WPT system, the CC and CV modes are achieved by varying the on-duty ratio of the buck converter. In addition, the proposed system also keeps the zero-voltage switching against coil misalignment and load variations without any information feedback from the rectifier to the inverter. This is because the load-independent behavior is built into the proposed system. The experimental results are consistent with the analytical predictions, which show the validity of the proposed circuit design strategy and the derived analytical expressions. Under rated conditions, the output power was 36.9 W and the power conversion efficiency was 86 % at the operating frequency of 6.78 MHz.

This paper presents an enhanced parasitic component model for spiral air-core inductors in MHz load-independent single-input multiple-output (SIMO) wireless power transfer (WPT) systems. The model improves upon previous designs by incorporating inductance, parasitic capacitance, and both parallel and series parasitic resistances, accounting for dielectric and copper losses. A prototype system featuring a load-independent class-EF inverter and multiple class-D rectifiers is developed to validate the model, demonstrating strong agreement between theoretical predictions and experimental results. The model ensures Zero-Voltage-Switching (ZVS) at the transmitter and constant output voltages at all receivers, offering a reliable framework for high-precision, high-frequency load-independent SIMO WPT system design.

In this research, we propose a variable-gain load-independent class-E rectifier with fixed input reactance for wireless power transfer (WPT) system. Featuring an adjusting network, the proposed rectifier can adjust its voltage gain to maintain a constant output voltage against load variations and coil misalignment, eliminating the need for additional regulators. Based on equations derived from circuit analysis, we present a design method to achieve the zero-voltage switching (ZVS) condition, ensuring high efficiency even at multi-MHz frequencies. Additionally, the input reactance of the proposed rectifier remains fixed, which is beneficial for maintaining ZVS of the inverter. To validate the design method, a WPT system at 6.78 MHz was built. The experimental results confirmed the successful voltage-gain adjustment to compensate for coil misalignment. Furthermore, load-independent ZVS and fixed input reactance were achieved, demonstrating the effectiveness of the proposed rectifier.

In wireless communication networks, it is difficult to solve many NP-hard problems owing to computational complexity and high cost. Recently, quantum annealing (QA) based on quantum physics was introduced as a key enabler for solving optimization problems quickly. However, only some studies consider quantum-based approaches in wireless communications. Therefore, we investigate the performance of a QA solution to an optimization problem in wireless networks. Specifically, we aim to maximize the sum rate by jointly optimizing clustering, subchannel assignment, and power allocation in a multiautonomous aerial vehicle-aided wireless network. We formulate the sum rate maximization problem as a combinatorial optimization problem. Then, we divide it into two subproblems: 1) a QA-based clustering and 2) subchannel assignment and power allocation for a given clustering configuration. Subsequently, we obtain an optimized solution for the joint optimization problem by solving these two subproblems. For the first subproblem, we convert the problem into a simplified quadratic unconstrained binary optimization (QUBO) model. As for the second subproblem, we introduce a novel QA algorithm with optimal scaling parameters to address it. Simulation results demonstrate the effectiveness of the proposed algorithm in terms of the sum rate and running time.

This paper proposes a machine learning (ML)-based design for a load-independent (LI) wireless power transfer (WPT) system. The proposed design strategy formulates the WPT design as an optimization problem and solves it by fully-numerical computation to achieve high-frequency LI operation. A multi-objective evaluation function is given to achieve the LI operation, which evaluates output voltage, power-delivery efficiency, and total harmonic distortion. The class-EF WPT system designed using the proposed method achieved narrower output voltage variations and higher power-delivery efficiency than the analysis-based design system. Additionally, the proposed design algorithm identifies parameter sets that were never found through the analysis-based design. Namely, only a small amount of current flows through the previous harmonic resonant filter of the class-EF inverter. These results demonstrate the potential of ML-based design in the field of power electronics.

Online multi-task allocation has become an essential research topic in Mobile Crowdsensing (MCS). Most existing studies merely focus on minimizing the total distance that workers need to travel, but ignore considering the total task rewards, which could lead to a reduction in the willingness of workers to complete tasks. In this paper, to incentivize workers to participate in tasks and protect their privacy, we propose a Location and Reward Privacy-Preserving based Secure Task Allocation(LRPP-STA) scheme. First, we design a secure distance computation method to obtain the distance from the workers to the tasks under location privacy preserving. Second, considering fixed reward for the task, we propose a Fixed Rewarding Secure Task Allocation(FR-STA) scheme, where a secure utility calculation method is proposed to calculate the encrypted utility of the worker upon completing tasks under rewards privacy preserving, along with the path planning for workers to maximize the total utility of the system through an Extended Maximum-Utility Flow model(EMUF). Third, considering the situation of dynamic task reward adjusted by requesters based on the supply and demand relationship as well as the urgency of the task, we propose a Dynamic Rewarding Secure Task Allocation(DR-STA) scheme to optimize the task allocation for workers while improving requesters satisfaction. Finally, we theoretically analyze the security of location and reward privacy-preserving scheme, and conduct extensive experiments with real-world datasets to verify that the secure task allocation scheme is effective in improving the total utility of workers compared to other baseline online tasking schemes.

The fusion of IoT and Blockchain (i.e., IoT-Blockchain) promisingly revolutionizes numerous domains. However, IoT-Blockchain systems may face scalability challenges due to a large number of IoT devices and blockchain performance. Sharding, which divides the blockchain into smaller groups, offers a solution to enhance blockchain scalability. However, most previous sharding research typically considers even node distribution in a shard (i.e., a fixed node number). Hence, it may not capture the characteristics of IoT- Blockchain systems well, where nodes are diversely distributed. This paper investigates a new scenario of shards having unevenly distributed nodes, aiming to see the impacts of the scenario on sharding protocols. More specifically, we evaluate the BrokerChain protocol on the sharding-based emulation platform (i.e., BlockEmulator) in scenarios with even and uneven node distributions. The results show that the protocol performance degrades with the uneven node distribution, suggesting the need for a dynamic sharding protocol.

This paper presents the design of the class-Φ3power oscillator. The topology of the proposed power oscillator features the feedback network from the resonant capacitance, which allows for the application of wireless power transfer (WPT) systems. Furthermore, the required phase shift necessary for applying the proposed feedback network is achieved by employing the class-Φ3inverter, which has a finite input inductance. Closed-form design equations for the proposed power oscillator are provided, which allows a quick and intuitive design. An experimental verification is conducted with the prototype power oscillator. The measured power-conversion efficiency was 92.2 % with 70 W output power at 1 MHz operation. The experimental results agreed quantitatively with the analysis, which shows the validity of the design.

This study explores the intersection of neuroscience and computer science, focusing on the use of spiking neural networks (SNNs) to simulate the behavior of biological neurons. A neural network model based on the Izhikevich neuron model is proposed to simulate the local auditory network of crickets. The parameters of the neuron model are optimized based on evaluation functions and identified by Particle Swarm Optimization (PSO), aligning its input-output relationships with the observed cricket neuron responses. The results showed that the network successfully simulated the behavior of individual neurons, promising applications in fields like neural prosthetics.

Blockchain holds significant potential in addressing the security, privacy, decentralization, and interoperability challenges prevalent in the Internet of Things (IoT), However, this advancement often comes at the expense of scalability. Therefore, enhancing the scalability of IoT blockchain systems while preserving other essential blockchain attributes is imperative. This paper aims to mitigate network latency in the blockchain network, a factor directly linked to blockchain scalability. Achieving this goal requires implementing an efficient peer selection method, moving beyond the reliance on default selection (i.e., the one in Bitcoin, Ethereum, etc.). In existing literature, Perigee has been introduced as a method that nearly optimizes the delay in the transaction transmission process. However, Perigee has not comprehensively addressed the complete transaction life cycle, which includes a crucial process-block transmission. In response to this limitation, we propose Dual Perigee, a solution that thoroughly considers and optimizes both transaction-oriented latency (TOL) and block-oriented latency (BOL). To show the effectiveness of Dual Perigee, we implemented and evaluated it within an emulated IoT-Blockchain system, comparing its performance with Perigee and the default peering method in Ethereum. The results reveal that Dual Perigee excels in reducing BOL compared to Perigee. Moreover, Dual Perigee exhibited a latency that was 43% and 80% lower than the default peering method and Perigee, respectively.

This paper proposes the load-independent (LI) class-E frequency multiplier along with a unified circuit analysis method with the LI class-E amplifier. A circuit-parameter determination strategy is presented to achieve LI operation and maximum power output capability at the rated condition. We designed the class-E amplifier and frequency doubler using the unified analytical expressions. Both the implemented circuits achieved the LI operation, namely constant output voltage amplitude and zero-voltage switching against load variations without any control. The experimental results showed quantitative agreements with the analysis results, namely waveforms and power conversion efficiency, which indicates the validity of the derived analytical expressions and design procedure.

Sparse Mobile CrowdSensing (SMCS) effectively lowers sensing costs while maintaining data quality, offering an alternative approach to data collection. Unfortunately, the fact that data contain sensitive information raises serious privacy concerns. Local Differential Privacy (LDP) has emerged as the de facto standard for ensuring data privacy. However, the LDP based on the perturbation concept causes a substantial reduction in the data utility of the SMCS system. To address this problem, we propose a novel scheme named enhancing Sparse mobile crowdsensing With manifold Optimization and differential Privacy (SWOP). Specifically, we first revisit the Gaussian mechanism based on the fact that data utility intervals are ubiquitous in sensing tasks, and introduce a novel perturbation mechanism, namely Truncated Gaussian Mechanism (TGM). Subsequently, we perturb user-collected data by locally injecting noise sampled from TGM and deduce a sufficient condition for the scale parameter to ensure ϵ-LDP. Furthermore, we model the data inference with privacy-preserving properties as an unconstrained optimization problem on a Riemannian manifold and solve it using the nonlinear conjugate gradient method. Extensive experiments on large-scale real-world and synthetic datasets are conducted to evaluate the proposed scheme. The results demonstrate that SWOP can greatly enhance the utility of data inference while ensuring workers’ data privacy compared to baseline models.

This paper proposes a load-independent high-frequency wireless power transfer (WPT) system for multiple receivers with a single transmitter. The proposed system achieves zero-voltage switching (ZVS) at the transmitter and constant output voltages at all the receivers against load variations without any control. Moreover, the proposed system keeps the load-independent operation even when the number of receivers changes. The circuit analysis for the proposed WPT system is given. Experimental verifications for the proposed WPT systems with two receivers were conducted, which showed the effectiveness. The implemented WPT system achieved a peak efficiency of 83.4% at 6.78 MHz and total output power of 50 W.

This paper presents a simulator-based design-optimization software for high-frequency power-electronics circuits, which consists of the heuristic algorithm, magnetic-component design tool, and commercial simulator, SPICE. Because we can use the SPICE component library, the software suggests high-accurate design results, and the experimental adjustments can be reduced. Besides, by using the heuristic algorithm, the optimization algorithm converges stably. The magnetic-component design tool provides a precise estimation of the power losses, which is important for high-frequency power-electronics circuit designs. As an example, we design the class-DE inverter by applying the developed software, which shows the usefulness of the software.

This study proposes a self-tuned series resonant power oscillator capable of load-independent operation. The proposed power oscillator has a self-tuning feedback loop that provides a gate-driving voltage with a constant phase shift and amplitude. Therefore, it is robust against component tolerances in a series resonant filter. It is also robust against load variations owing to its load-independent design. Consequently, it maintains a high-efficiency and constant AC output against load variations and component tolerances. Experimental results demonstrated the effectiveness of the proposed power oscillator.

In recent IEEE 802.11 WLANs, an Access Point (AP) can use the Channel Bonding (CB) technique to increase the transmission bandwidth. Given limited bandwidth resources, it is not trivial to allocate channels for densely deployed APs to fairly meet their diverse traffic demands. In general, the non-overlapping channel allocation approach has been proven to be an ideal solution for maximizing the achievable throughput of WLANs using CB. However, we argue that the approach is no longer efficient because of two common situations: i) insufficient non-overlapping channels and ii) imbalanced traffic demands. Instead, the overlapping channel allocation is more suitable in such situations. In this study, we first apply a continuous-time Markov Chain (CTMC) model to analyze the effect of overlapping channel allocations for neighboring APs under unsaturated traffic conditions. Based on the analysis results, we propose a novel channel allocation algorithm based on the Bin-Packing Problem (BPP) that maximizes the fairness of the throughput-to-demand satisfaction ratio between APs. Through simulations, we demonstrated that the proposed algorithm can achieve near-optimal performance in various network settings. The algorithm also outperformed existing algorithms with the same overlapping channel approach.

This paper introduces a host-based method for investigating IPv6 adoption and performance in academia that targets universities in Japan and Vietnam. Unlike other works, the investigation has been utilized on a host native IPv6 host with a standard tool (i.e., curl). We first probe the IPv6 capabilities of the universities’ websites. Second, within the IPv6-supported websites, we compare the performances of IPv4 and IPv6 when letting the two IP versions access the websites concurrently. We find that, despite the popularity of IPv6 in the two countries, a significant number of academic websites are not yet IPv6 capable. The native IPv6 client can only access fifty of the more than one thousand websites in Japan. Furthermore, there are no IPv6-supported websites at Vietnamese universities. Among the accessible IPv6 websites in Japan, we observe that the web access performances of IPv4 and IPv6 are similar.

In this research, a novel load-independent Class-E/F inverter with constant voltage (CV) and constant current (CC) output modes is proposed. By adding one auxiliary switch to the class-E/F inverter, the proposed inverter can change into the class-E topology. A components design method is proposed to achieve load-independent conditions for both topologies by merging the design conditions of the load-independent class-E and class-E/F inverters together. Therefore, the proposed inverter can switch between CV and CC output modes against load changes at the same switching frequency. Additionally, zero-voltage switching (ZVS) can be maintained for both modes despite load variation. The proposed inverter has a simplified topology, making it suitable for minimized wireless power transfer applications as the transmitter part. A 1 MHz experimental prototype circuit was designed and implemented. A circuit experiment was conducted, which confirmed the usefulness of the proposed inverter.

We propose a new “wire-free robotic system” applicable to an articulated robot that realizes both control and power lines wirelessly at the same time in the joints. The wire-free robotic system consists of a wireless communication system, a wireless power transfer system, and a robot operation system. Control lines are realized by wireless communication in the 60 GHz band with selection-based transmission site diversity. Power lines are realized by wireless power transfer of the magnetic resonance method with load-independence. We developed a prototype robot and verified the communication quality and the operation. It is confirmed that the prototype robot can achieve more than 99% of packet delivery ratio in almost all operating areas. It is also confirmed that the prototype can be controlled and powered wirelessly.

Blockchain technologies have been emerging with the potential to disrupt many fields (e.g., cryptocurrencies replacing the traditional ones, enabling trustworthy voting, etc.). The Internet of Things (IoT) has been predictably strengthened when integrating to the private blockchain, such as Ethereum. In an IoT deployment with private Ethereum, a thorough understanding of the latency is a critical issue that has not been adequately understood in the literature. Motivated by that, this work aims to comprehend the latency performance in the IoT Ethereum with two popular consensus algorithms: Proof of Work (PoW) and Proof of Authority (PoA). Initially, we clarify different latency segments from transaction submission to execution, namely, the transaction lifecycle in a private blockchain. We then consider the three related latency metrics: 1) transaction-oriented latency; 2) mining time; and 3) block-oriented latency in the PoW case. With PoA, the mining time’s consideration is omitted since the mining process is not necessary. After that, we construct a realistic private Ethereum IoT network (i.e., using a laptop and seven Raspberry Pi 3b+ nodes) and a large-scale emulated one with 30 nodes. We write and deploy a smart contract to read and write data to the blockchain and measure the latencies in various scenarios. The measurement results reveal the values of transaction-oriented and block-oriented latency with PoW and PoA in both the actual and emulated networks. Moreover, we derive the expected value for the PoW’s mining time by fitting the probabilities to an exponential curve.

This paper tackles the problem of using and paying a network service with guaranteed quality of service (QoS) at a fine granularity in the future wireless network. We propose the IOTA-based QoS guaranteed Flow system (IQF), where a user and service provider can exchange the IOTA cryptocurrency for the guaranteed network resources, such as latency and bandwidth. First, IQF uses the IOTA Tangle, a lightweight, efficient distributed ledger technology, for its payment and transaction record. Second, IQF adopts Software Defined Networking to realize the guaranteed delay and bandwidth provision. We have implemented the IQF systems using the mininet-wifi emulator, an SDN controller (i.e., POX), and IOTA clients. Moreover, we have evaluated the service provisioning algorithms with a micropayment of IQF with the test Tangle (i.e., comnet). The evaluation results show that IQF has successfully achieved the delay and bandwidth provision with all the transactions stored in comnet.

This paper presents a 2-hop wireless power transfer (WPT) system for the robot-arm application. The proposed WPT system consists of the class-E inverter on the transmitter side and a class-D rectifier on the receiver side. We obtain the analytical model of the WPT system for obtaining the class-E ZVS/ZDS conditions. The model includes the detailed physical information of the coil, namely coil diameter, height, wire thickness, winding turn number, and so on. Therefore, it is possible to optimize the WPT system for the theoretical highest power-delivery efficiency under the robot-arm coil-space restriction. The circuit experiment showed quantitative agreements with the theoretical predictions, which proved the validity of the proposed design method. The experimental prototype achieved 78.0 % power-delivery efficiency at 6.78 MHz operating frequency and 39.3 W output power.

Advances in communication and sensing technologies have enabled low-cost air quality monitoring devices that are easy to deploy. Moreover, the diverse deployment of the devices, which share a huge amount of sensing data, may help monitor and predict air quality at a fine grain granularity. In such context, valuing the data and introducing micropayment may encourage more people to install monitoring devices and share their data. More specifically, the micropayment, a small amount of electronic currency, will be paid for each portion of shared sensing data. To this end, IOTA cryptocurrency shows potential due to its high-speed transactions without transaction fees. This paper introduces a novel IOTA-based micropayment system for air quality monitoring applications. Our system allows IoT devices (i.e., Raspberry Pi) running IOTA clients to exchange the data on the public IOTA network (i.e., the Tangle). We also implement IOTA nodes, which can join the public IOTA or form a private IOTA. Our system has been proven to work well with real air quality monitoring devices. We have also evaluated various system performance parameters, including latency, jitter, and throughput.

The fifth generation of mobile wireless networks (5G) will provide an infrastructure with abundant and reliable connectivity for innovative and complicated applications. In 5G, 5G mobile devices, which will have improved computing resources for such applications, play an essential role. However, the network stack of 5G devices may continue to be borrowed from 4G legacy operating systems, thereby degrading user experience. In this paper, we posit that 5G users should have flexibility in utilizing networks and gain more awareness of network selection. To this end, we exploit network softwarization technologies to empower 5G devices. We then devise 5GSoft, a novel softwarized networking stack on each 5G mobile device. 5GSoft includes wireless virtualization to relax the dependence on hardware, thereby enabling sharing and multiple access. The 5GSoft device can concurrently exploit surrounding wireless networks using software-defined networking. Finally, the 5GSoft device is aware of network selection for each application process by applying network namespace. Qualitative evaluation of 5GSoft, in comparison to other approaches, highlights its effectiveness in terms of awareness and flexibility provision. Moreover, real experiments show that the virtualization in 5GSoft has negligible overhead.

There is an inherent reliance on collaboration among the participants of mobile ad hoc networks in order to achieve the fixed functionalities. However, they are susceptible to the destruction of the malicious attacks or denial of cooperation. Therefore, it becomes obvious that the security issue is urgently needed to be addressed. Over the last few years, many trust-considered countermeasures have been proposed. The design of trust quantification methods is the key of these countermeasures. In this study, we abstract a novel light-weight subjective trust inference framework, which is divided into trust assessment and trust prediction. The process of node trust assessment is based on node's historical behaviours. Then utilizing the obtained trust data sequence, we introduce the SCGM(1,1)-weighted Markov stochastic chain measure to predict node's trust for future decision making. Experimental results have been conducted to evaluate the effectiveness of the proposed trust model. As an important security application, based on the standard On-Demand Multicast Routing Protocol (ODMRP), we make four major improvements which take the issue of trust into consideration, and propose a novel trust-based routing protocol called the On-Demand Trust-Based Multicast Routing protocol (ODTMRP). And finally, convincing experimental results are presented using three routing evaluation metrics.

The dawn of 5G is rising with emerging wireless and network technologies that promisingly transform various aspects of human lives. The 5G mobile devices are going to tightly engage with the 5G infrastructure for future applications such as virtual reality, AI-enabled applications, etc. However, we argue that the tight engagement with convenience may bring downside that is a user may not correctly control/own her/his device. In particular, the user may not have the flexibility in utilizing networks, as well as, be aware of the network selection. This paper introduces a novel networking stack for 5G mobile devices (namely 5GVir) that leverages virtualization techniques for flexibility and awareness. The 5GVir device can concurrently exploit surrounding wireless networks by using Software Defined Networking (SDN). SDN provides a rich set of flexibility feature that will meet user expectation. Moreover, 5GVir includes wireless virtualization that can relax the dependence on hardware as well as provides a wireless link for the SDN's control channel. Last but not least, the 5GVir device has an additional awareness feature aware that drives each application process to predetermined networks (i.e., applying network namespace). Our prototype shows the potential of realizing 5GVir. Moreover, the initial experiments show that the virtualization in 5GVir has negligible overhead.

This paper presents an easy-to-use analytical design approach of the load-independent class-E inverter at any duty ratio. By using the analytical approach, it is possible to maintain the amplitude of the output voltage and the operation of the zero-voltage switching. Additionally, a design example is given along with its LTspice simulation and laboratory experiment. The LTspice simulation and laboratory experiment waveforms are in good agreement with the analytical ones even load variations. Moreover, all the switch-voltage waveforms satisfy the ZVS condition. These results showed that the proposed approach and analytical expressions are available and effective.

This paper considers wireless string-topology multi-hop networks, in which each network node operates autonomously following the IEEE 802.11 Distributed Coordination Function (DCF). The IEEE 802.11 DCF defines multiple transmission rates. In general, the transmission rate is inversely proportional to the transmission distance. The carrier-sensing distance, however, is independent of the transmission rate under the condition of identical transmission power. Therefore, when the transmission rate amplifies, the number of nodes within the carrier-sensing range may increase; hence affect the network performance. The previous works either simplify or have no consideration of the effect. Addressing the issue, we newly propose an analytical expression of end-to-end throughputs of IEEE 802.11 string-topology multi-hop networks, taking into account transmission rates. The validity of the proposed analytical model is confirmed from the quantitative agreements with the simulation results.

This paper presents a novel analysis procedure for the class E oscillator. A design example is given along with the LTspice-simulation and experimental waveforms. All the switch-voltage waveforms from the LTspice simulation and circuit experiment satisfy the class E zero-voltage switching (ZVS) and zero-voltage-derivative-switching (ZVDS) conditions. It is seen from the LTspise-simulation and experimental results that the analytical prediction agreed with the simulated and experimental ones quantitatively, which validated the accuracy and effectiveness of the proposed design procedure. The efficiency achieved 94.6 % at 7.8 W output power and 1 MHz operating frequency.

This paper presents steady-state analytical expressions of the class-D zero-voltage switching (ZVS) inverter with asymmetrical duty-cycle control for wireless power transfer applications. In the asymmetrical duty-cycle control, the output current contains harmonic components. The obtained analytical expressions consider harmonic components of output current. Additionally, MOSFET anti-parallel diode effect is included in the analytical expressions for expressing the ZVS operation. As a result, the analytical expressions of the steady-state waveforms can be obtained with high accuracy. This paper also shows the control strategies against load variations, which is one of the applications of the analytical expressions. The validity of the analytical expressions was confirmed from quantitative agreements with experimental waveforms.

This paper presents a wireless power transfer system with the asymmetrical duty-cycle controlled class-D zero-voltage switching (ZVS) inverter and class-E rectifier along with its analytical expressions and the design procedure. In the asymmetrical duty-cycle control, the resonant current of the inverter contains harmonic components. In the analysis, harmonic components of resonant current are considered. Additionally, MOSFET anti-parallel diode effects are included in the analytical expressions for expressing the ZVS operation. As a result, the accurate steady-state waveforms can be obtained from the analytical expressions. This paper also shows the control strategy against load variations, which is one of the useful applications of the analytical expressions. The validity of the analytical expressions and the effectiveness of the proposed control strategy were confirmed by a quantitative comparison with experimental waveforms.

This paper presents a high-speed resonant driver for silicon carbide (SiC) MOSFET, which is based on the class-E inverter. Gate-to-source resistance and input capacitance of SiC MOSFET are included in the resonant circuit of the driver for avoiding the driving-signal strain. Additionally, clamp diodes are added to the output filter in the proposed driver, which makes a square-waveform-like driving signal. The design example along with experimental waveforms is shown in this paper. It was possible in the laboratory experiments to drive the SiC MOSFET at 7 MHz and 13 MHz frequencies with satisfying the zero-voltage switching condition, which showed validity and effectiveness of the proposed driver and its design procedure.

This paper presents a design procedure for wireless power transfer (WPT) systems based on the class-E2 dc-dc converter, taking into account inductive coupling-coil optimizations. The WPT system model is formulated as an equivalent circuit model by expressing the inductive coupled part as a transformer with low-coupling coefficient and equivalent resistances of primary and secondary coils. By using the circuit model, the dc-to-dc efficiency can be obtained analytically. The dc-to-dc efficiency, which is a cost function for optimization, is expressed as functions of physical parameters, such as coil size, wire type, and number of turns. The particle swarm optimization (PSO) is applied for reduction of the computational complexity compared with previous design method [1] and maximization of the cost function in this paper. Experimental results showed the validity and the usefulness of the proposed design procedure.

The following closed-loop transfer functions of the boost converter operating in continuous-conduction mode (CCM) supplying a complex impedance load are derived and analyzed: input-to-output voltage Mvcland reference-to-output Tcl. The load of the boost dc-dc converter is composed of a series-connected resistance and inductance. The dynamic characteristics of the closed-loop boost converter with a third-order double-lead integral compensator are evaluated for different load inductances. The theoretically predicted results are validated through switching-circuit simulations using a suitable converter design example.

We propose a light-weight performance analysis of Wi-Fi offload using a simple Markov model. Although the proposed model does not describe the behavior of the contention window of each station in detail, it allows us to analyze the non-saturation throughput while considering interaction among interfering stations and the queueing behavior of each station. In addition to this, the proposed model does not need to use the assumption that frames arrive at relay station according to a Poisson process. In this paper, we show how to apply the mean field approximation to the model to significantly reduce the amount of computation. We show that the proposed model accurately estimates the throughput performance of the Wi-Fi offload, and that the mean-field approximation is still valid in the scenario of the Wi-Fi offload.

This paper presents a RIC-WPT system with class-E inverter and class-DE rectifier along with its analytical design procedure. By using the class-E inverter as a transmitter and the class-DE rectifier as a receiver, the designed WPT system can achieve a high power-delivery efficiency because of the class-E ZVS/ZDS conditions in both the inverter and the rectifier. In the experimental results, the system achieved 73.0 % overall efficiency at 9.87 W (50 Ω) output power, coil distance 10 cm, and 1 MHz operating frequency. The experimental results showed good agreement with the design specifications, which indicates the validity of the design procedure.

This paper proposes the analytical expressions for the IEEE 802.11 string-topology multi-hop networks using Markov-chain model. For achieving that, the proposed analysis procedure includes two proposals, which are: (i) Bianchi's Markov-chain model is modified for considering a relationship between the backoff timer and frame length, and (ii) the interferences, such as hidden node collision and carrier sensing, among network nodes are expressed by merging the proposed Markov-chain model and airtime expression. The analytical expressions are verified by comparisons with simulation results.

This paper proposes a numerical algorithm for drawing distribution maps of switching power-converter characteristics on parameter spaces. The concept of the proposed algorithm is that parameters satisfying the assigned conditions are derived and followed with low computation cost. Zero-Voltage-Switching (ZVS) region, output power distribution map, and contour map of power-conversion efficiency of the phase-controlled class-D inverter are drawn as application examples of the proposed algorithm. It is possible from these maps to design the phase-controlled class-D inverter achieving the ZVS at entire control regions. The validity and effectiveness of the proposed algorithm were confirmed by carrying out circuit experiments.

A new family of Class D resonant inverters is proposed in this paper. Multiple identical series resonant inverters are paralleled using intercell transformers to form phase-controlled multiphase resonant inverter with a common resonant circuit. Inverters can operate at constant frequency utilizing phase-shift control to regulate output. A frequency-domain analysis of the proposed family is performed. An experimental prototype of a three-phase resonant inverter with common resonant circuit was built and extensively tested at an output power of 550 W and switching frequency of 167 kHz.

This paper presents a resonant inductive coupling wireless power transfer (RIC-WPT) system with a class-E2dc-dc converter along with its analytical design procedure. By using the class-E inverter as a transmitter and the class-E rectifier as a receiver, the designed WPT system can achieve a high power-conversion efficiency because of the class-E ZVS/ZDS conditions satisfied in both the inverter and the rectifier. In the simulation results, the system achieved 65.9 % overall efficiency at 5 W (50 Ω) output power, coil distance 30 cm, and 5 MHz operating frequency. Additionally, the simulation results showed good agreement with the design specifications, which indicates the validity of the design procedure.

This paper proposes an inductive coupled wireless power transfer (WPT) system with class-DE transmitter and class-E rectifier along with numerical design procedure. The proposed WPT system can achieve high power-transfer efficiency at high-frequencies because both the transmitter and the rectifier satisfy the class-E ZVS/ZDS conditions. By using numerical design procedure, it is possible to design the WPT system without analysis of the circuit and consideration of the impedance matching. By carrying out the circuit experiment, the validity of the design procedure and effectiveness of the proposed WPT system were confirmed. The laboratory measurement showed the 90.4 % overall power-transfer efficiency with 100 W output at 500 kHz operating frequency.

This paper presents analytical expressions of the MOSFET-parasitic-capacitance effects on the output envelope of the EER transmitter, taking into account the MOSFET linear gate-to-drain and nonlinear drain-to-source parasitic capacitances in the class-E amplifier. The analysis is useful to predict the behavior of the EER transmitter using the class-E amplifier. It is shown that the envelope of the output voltage is not in proportion to the dc-supply voltage due to the MOSFET-parasitic-capacitance effects. Additionally, the driving voltage waveform affects the output-voltage amplitude and phase shift between the driving voltage and the output voltage.

In this paper, we propose a numerical method to calculate the grazing bifurcation points in an impact oscillator with periodic boundaries. First, we illustrate the n-dimensional autonomous impact oscillator with the moving boundaries. The boundaries consist of the scalar function involving the periodic function. When the trajectory hits one boundary, the solution jumps to the other immediately. Next, we construct the composite Poincaré map and show its derivatives. Using the derivatives, we calculate the location of the periodic point, bifurcation parameter and time that elapses before the trajectory hitting the boundary. Finally, we apply the method to a Rayleigh-type oscillator with the sinusoidal boundaries to confirm its validity.

This paper proposes a MAC protocol for ad hoc networks with directional antennas for mitigating the directional hidden-node problem. In the proposed protocol, it is possible to tell the communication situation to the directional hidden node by using DATA-frame fragmentations and short busy advertisement signals. As a result, the frame collisions induced by the directional hidden nodes can be reduced and the network throughput is enhanced compared with the conventional protocol. Simulation results show the validity and effectiveness of the proposed protocol.

This paper gives analytical expressions for the output power and the power conversion efficiency of the class-E power amplifier outside the class-E ZVS/ZDS switching conditions. The analytical predictions agreed with the experimental results quantitatively, which indicates the validity of the analytical expressions. Moreover, a design example applying the analytical expressions for the power conversion efficiency is given. By using the analytical expressions, it is possible to design the class-E amplifier, which improves the power conversion efficiency compared with that of the class-E amplifier satisfying the class-E ZVS/ZDS conditions.

In this paper, we present analytical expressions for the waveforms and design equations for achieving the ZVS/ZDS conditions in the class-E power amplifier, taking into account the gate-to-drain parasitic capacitance of the MOSFET. We also give a design example along with PSpice simulation and experimental results. The voltage waveforms obtained from both the PSpice simulation and the circuit experiment achieved the class-E ZVS/ZDS conditions completely, which verify the analytical expressions. The results in this paper indicate that it is important to consider the effect of the MOSFET gate-to-drain capacitance for achieving the class E ZVS/ZDS conditions. The experimental power conversion efficiency achieved 92.8 % at output power Po= 4.06 W and operating frequency f = 7 MHz.

Collaborative filtering (CF) is one of the most popular recommender system technologies. It tries to identify users that have relevant interests and preferences by calculating similarities among user profiles. The idea behind this method is that, it may be of benefit to one's search for information to consult the preferences of other users who share the same or relevant interests and whose opinion can be trusted. However, the applicability of CF is limited due to the sparsity and cold-start problems. The sparsity problem occurs when available data are insufficient for identifying similar users (neighbors) and it is a major issue that limits the quality of recommendations and the applicability of CF in general. Additionally, the cold-start problem occurs when dealing with new users and new or updated items in web environments. Therefore, we propose an efficient iterative prediction technique to convert user-item sparse matrix to dense one and overcome the cold-start problem. Our experiments with MovieLens and book-crossing data sets indicate substantial and consistent improvements in recommendations accuracy compared with item-based collaborative filtering, singular value decomposition (SVD)-based collaborative filtering and semi explicit rating collaborative filtering.

The class-E ZVS/ZDS operation within the class-DE amplifier can be easily achieved by adding external shunt capacitances. This paper presents the analytical expressions for the design of the class-DE amplifier with the shunt capacitances composed of the linear and nonlinear capacitances for the switch-on duty ratio D=0.25. In the analysis, an equivalent linear shunt capacitance of nonlinear MOSFET output capacitance are defined and derived. The analytical results show good agreement with the experimental ones, which validates our analysis.

This paper investigates the design curves of the class DE amplifier with nonlinear shunt capacitances for any output Q and any grading coefficient m of the diode junction in MOSFET. The design curves are derived by the numerical calculation. It is clarified that the nonlinearities of shunt capacitances affect the design curves of the class DE amplifier, especially, for low output Q. The waveforms from Spice denote the validity of the design curves.

This paper presents an interleaved class E2dc/dc converter. In the proposed converter, N class E2dc/dc converters are connected in parallel at the class E rectifier. The proposed converter is suitable to the low-voltage/high-current applications. Since less current flows through the each converter, the amount of the power losses on the parasitic resistances are also reduced. In addition, the output filter of the rectifier is downsized because of higher frequency of the interleaved current. By carrying out the circuit experiments, we show that the experimental results agree with the numerical ones quantitatively. The laboratory measurement achieves the over 90% power conversion efficiency under 3.2W and 1MHz operation.

In this paper, we propose a blind frame-by-frame dereverberation using correlation coefficients considering periodicity of voiced speech. In the proposed method, the reference signal is derived by reducing speech periodicity from recovered signal of previous frame. The reference signal is used in order to estimate the impulse response in each frame. The recovered signal is obtained by using the estimated impulse response. From the investigation of performance evaluation, we show the proposed method is more effective than the conventional method in reducing reverberation without introducing speech distortion

Switching schemes have been studied for removing impulse noise. As a switching scheme, pixel-wise median of the absolute deviations from the median (PWMAD) detector was proposed. Since PWMAD detector uses only a single parameter, it is easy to optimize a parameter. However, PWMAD detector can not detect noisy pixels accurately when noisy pixels exist in neighborhood of edge pixels. In this paper, we propose an impulse noise detector using mathematical morphology. We use mathematical morphology in order to improve noise detection in neighborhood of edge pixels. Moreover, the proposed method requires only a single parameter by using mathematical morphology. Carrying out the simulation, we will illustrate the noise detection ratio of the proposed method, and show that it is more accurately to detect noisy pixels than PWMAD detector without increasing parameters.

This paper presents exact analysis of class DE amplifier for any conditions including outside optimum conditions. We give an analytical expression of waveform equations and initial values of current and voltage in the steady state. By using these analytical equations, switching voltage, output voltage and power conversion efficiency of class DE amplifier can be derived with few efforts. In this paper, we denote the steady state behaviors outside optimum conditions which occur by the variations of operating frequency and switch on duty ratio. The theoretical results show a quantitative agreement with the experimental ones, which denotes the validity of analytical equations.

Sliding mode control (SMC) has a strong capability of controlling nonlinear systems with uncertainties. However, it requires thorough knowledge of parameters and dynamics of the controlled plant, which are difficult to be obtained or may be unknown. This will cause difficulties in calculating equivalent control law of SMC. To overcome this problem, this paper proposes an adaptive SMC using simple adaptive control (SAC) developed for single-input single-output (SISO) nonlinear systems with unknown parameters and dynamics. The role of SAC is to construct an equivalent control input of adaptive SMC. To construct a corrective control input, this paper applies the method using the sign function with a modified sliding surface. Finally, the effectiveness of the proposed method is confirmed through computer simulation.

In this paper, we propose a novel method for multiuser detection (MUD) based on the branch-and-bound (BBD) method using user grouping. The proposed method partitions K users into M disjoint groups and applies the BBD method to each group. Due to this user grouping, the number of users for the BBD method applied to a group is less than K. Therefore, the worst-case computational cost of the proposed method can be reduced dramatically compared with that of the BBD method. For an improvement of the probability of group detection error (GDE), the user signals of other groups are removed in parallel by using a solution of the decorrelating decision-feedback detector (DDFD) that is applied to all users before the user grouping. Moreover, P candidate solutions are derived in each BBD method. Finally, the best solution is determined from all combinations of the P candidate solutions. It is clarified the worst-case computational cost of the proposed method is much less than that of the BBD method, which is within the possible range to be implemented in a practical system. The simulation results show that the average computational cost of the proposed method is same order as that of the BBD method and the DDFD. They also denote that the probability of GDE of the proposed method is larger than that of the BBD method, but smaller than that of the DDFD.

This work presents a compensating method based on a self-organizing map (SOM) of nonlinear distortion, which is caused by the high-power amplifier (HPA) in 16 QAM-OFDM systems. OFDM signals are sensitive to nonlinear distortions and different methods are studied to limit them. In the proposed scheme, the correction is done at the receiver by a SOM algorithm. Simulations are carried out considering an additive white Gaussian noise (AWGN) transmission channel. Simulation results show that the SOM algorithm brings perceptible gains in a complete 16 QAM-OFDM system.