Beom Kwon

Joint Energy Management System of Electric Supply and Demand in Houses and Buildings

In this paper, a joint scheduling scheme for the electric supply and demand of Home Energy Management System (HEMS) and Building Energy Management System (BEMS) via energy management in houses and buildings is presented. To reflect ongoing policy, the Korea Electric Power COoperation (KEPCO) tariff is employed to formulate the optimization problem in terms of the sequential management procedure of prediction, supply control and demand control. As a result, an optimal electric supply pattern to produce the minimum energy cost can be obtained under a given curtailment. From simulation, the proposed scheduling scheme demonstrates greater reliability and adaptation for the interruptible load (IL) than the day-ahead method.

BUCKET: Scheduling of Solar-Powered Sensor Networks via Cross-Layer Optimization

Renewable solar energy harvesting systems have received considerable attention as a possible substitute for conventional chemical batteries in sensor networks. However, it is difficult to optimize the use of solar energy based only on empirical power acquisition patterns in sensor networks. We apply acquisition patterns from actual solar energy harvesting systems and build a framework to maximize the utilization of solar energy in general sensor networks. To achieve this goal, we develop a cross-layer optimization-based scheduling scheme called binding optimization of duty cycling and networking through energy tracking (BUCKET), which is formulated in four-stages: 1) prediction of energy harvesting and arriving traffic; 2) internode optimization at the transport and network layers; 3) intranode optimization at the medium access control layer; and 4) flow control of generated communication task sets using a token-bucket algorithm. Monitoring of the structural health of bridges is shown to be a potential application of an energy-harvesting sensor network. The example network deploys five sensor types: 1) temperature; 2) strain gauge; 3) accelerometer; 4) pressure; and 5) humidity. In the simulations, the BUCKET algorithm displays performance enhancements of ~12-15% over those of conventional methods in terms of the average service rate.

Prototype filter design for QAM-based filter bank multicarrier system

In this paper, we provide conditions for a prototype filter design of filter bank multicarrier (FBMC) based on quadrature amplitude modulation (QAM). The conditions consist of a generalized Nyquist criterion (GNC) for nearly perfect reconstruction (NPR) and meeting the stopband condition for a small side-lobe. In a practical environment, a small side-lobe is a key aspect of achieving high spectral efficiency, which becomes an important factor in reducing the size of the guard band among channels. In addition, because the conventional GNC is derived under the assumption of an ideal channel, which can be easily broken over a practical multipath channel, we propose a relaxed NPR that considers the multipath delay using a 2L-oversampled discrete Fourier transform (DFT) in the frequency domain. Based on the relaxation of the GNC depending on a multipath channel, we formulate an optimization problem for a QAM-FBMC prototype filter design and propose a prototype filter with a small side-lobe and reliable BER performance. Simulation results show that the proposed prototype filter remarkably reduces the side-lobe compared to conventional QAM-FBMC based on two types of prototype filters and orthogonal frequency division multiplexing (OFDM) via the trade-off between GNC and side-lobe performance. The benefit of the side-lobe condition allows the proposed prototype filter, the Relaxed-NPR-F, to improve spectral efficiency by reducing the guard band in the frequency domain.

Implementation of a Virtual Training Simulator Based on 360° Multi-View Human Action Recognition

Virtual training has received a considerable amount of research attention in recent years due to its potential for use in a variety of applications, such as virtual military training, virtual emergency evacuation, and virtual firefighting. To provide a trainee with an interactive training environment, human action recognition methods have been introduced as a major component of virtual training simulators. Wearable motion capture suit-based human action recognition has been widely used for virtual training, although it may distract the trainee. In this paper, we present a virtual training simulator based on 360° multi-view human action recognition using multiple Kinect sensors that provides an immersive environment for the trainee without the need to wear devices. To this end, the proposed simulator contains coordinate system transformation, front-view Kinect sensor tracking, multi-skeleton fusion, skeleton normalization, orientation compensation, feature extraction, and classifier modules. Virtual military training is presented as a potential application of the proposed simulator. To train and test it, a database consisting of 25 military training actions was constructed. In the test, the proposed simulator provided an excellent, natural training environment in terms of frame-by-frame classification accuracy, action-by-action classification accuracy, and observational latency.

Iterative Interference Cancellation and Channel Estimation in Evolved Multimedia Broadcast Multicast System Using Filter-Bank Multicarrier-Quadrature Amplitude Modulation

We propose a new channel estimation method based on filter-bank multicarrier-quadrature amplitude modulation (FBMC/QAM) for use in evolved multimedia broadcast multicast systems (eMBMSs). To achieve this goal, we use two different prototype filters to satisfy the orthogonality conditions for even and odd subcarriers. Orthogonality conditions cannot, in practice, be guaranteed using only two filters because they generate residual interference, including intercarrier and intersymbol interference, which makes it difficult to obtain accurate channel coefficients at reference symbols and leads to degraded channel estimation and bit error rates (BERs). To reduce the influence of residual interference on channel estimation, we model residual interference in a closed form over a multipath channel. Based on this approximated residual interference, the interference is effectively cancelled with respect to the reference, thereby significantly improving the FBMC/QAM-based eMBMS performance. Simulation demonstrates that the proposed method improves the mean squared error, BER, and the effective data rate.

Implementation of Human Action Recognition System Using Multiple Kinect Sensors

Human action recognition is an important research topic that has many potential applications such as video surveillance, human-computer interaction and virtual reality combat training. However, many researches of human action recognition have been performed in single camera system, and has low performance due to vulnerability to partial occlusion. In this paper, we propose a human action recognition system using multiple Kinect sensors to overcome the limitation of conventional single camera based human action recognition system. To test feasibility of the proposed system, we use the snapshot and temporal features which are extracted from three-dimensional (3D) skeleton data sequences, and apply the support vector machine (SVM) for classification of human action. The experiment results demonstrate the feasibility of the proposed system.

A Target Position Decision Algorithm Based on Analysis of Path Departure for an Autonomous Path Keeping System

To realize a path keeping system (PKS), it is essential to guide autonomous vehicle (AV) to a desired direction while maintaining safety. To maintain a desired driving path, it is necessary for an AV to perceive its surrounding environment by gathering directional information while traveling. Therefore, precise localization of an AV and autonomous guidance are essential technologies for the successful implementation of a PKS. As a type of radio guidance, an AV can use trilateration to identify its location relative to three reference positions by measuring the strength, time, or time difference of the reception of transmitted radio signals. Direction of arrival (DOA) techniques can also be used to estimate the direction of a signal emitted from a transmitter, and this information can be used to set the driving direction of an AV. However, in a practical environment, estimation errors may arise when the AV estimates its location or the direction of signal emitted from a transmitter, and these errors may cause the problem of path departure. To address this problem, we conducted a mathematical analysis to identify potential errors in estimating location and direction. Herein we propose a target position decision algorithm for PKS, which uses trilateration and DOA (PKS-TnD) to drive an AV in a desired direction to avoid path departure. By using this algorithm, an AV calculates its next target position based on the error constraints of trilateration and DOA by means of numerical analysis. Additionally, an energy efficiency problem is also formulated herein and energy use is optimized by using a Lagrangian equation.

Virtual MIMO broadcasting transceiver design for multi-hop relay networks

To improve end-to-end throughput and to reduce signaling overhead in multi-hop relay networks, broadcast virtual multiple-input and multiple-output (MIMO) systems (BVMSs) have been introduced. Conventionally, this research has been done for a limited environment where each node is equipped with a single-antenna and also interference from other networks is not included for the numerical analysis. In this paper, we propose a new virtual MIMO broadcasting transceiver (VMBT) to overcome the limitation of conventional BVMS and to improve end-to-end throughput for BVMS-based multi-hop-relay networks while the signaling overhead effectively reduced. Toward this goal, proposed VMBT is designed based on the following contributions: analysis of the channel ellipse property, convergence proof of the iterative algorithm and utilization of the null and span of channel vectors. The simulation results show that the proposed VMBT achieves the highest end-to-end throughput compared with that of other conventional technologies.

Optimal Flow Rate Control for SDN-Based Naval Systems

It is essential for a naval ship system (NSS) to transmit important information with very low delay for successful network-centric warfare under given time constraints. From this perspective, quality of service (QoS) control and low delay transmission are the most important components to improve efficient network utilization in NSSs. In general networks, conventional network algorithms have been optimized to manage network devices such as gateway, switch, bridge, hub, and router in a distributed manner for ease of plug-in and play operation, but which may not be optimal for the NSS. This is because, unlike the general network environment, the NSS is equipped with various nodes, which need to be operated through a centralized hierarchical network structure in accordance with their priorities. Thereby, it is difficult to apply new network algorithms to the NSS due to the closed network environment. To overcome this limitation, we propose a novel NSS employing software defined network (SDN) technology. A novel algorithm called real-time transmission via flow rate control (RTF) is proposed for the SDN-based NSS to optimize the specific environment of NSS. In the proposed algorithm, the optimal flow rates of nodes and network devices are obtained via dual decomposition in conjunction with requirements of delay and QoS. The proposed algorithm obtains the optimal solution iteratively while measuring the performance with traffic models based on real data measured in NSS. Through simulation using Floodlight, we demonstrate that RTF significantly contributes to improving throughput in real-time transmission compared with conventional algorithms. The proposed algorithm improves the average throughput by up to 11.8% while guaranteeing real-time transmission.

Effective Interference Nulling Virtual MIMO Broadcasting Transceiver for Multiple Relaying

In multi-hop relay networks, the improving end-to-end sum rate is a challenging issue. Although a new cooperative beamforming called virtual multiple-input multiple-output (MIMO) has been introduced as a possible solution, conventional virtual MIMO systems have severe signaling overhead among master and source nodes when the number of hops increases. To resolve this problem, a broadcast virtual MIMO system and a virtual MIMO broadcasting transceiver (VMBT) have been proposed to reduce the computational complexity and improve the end-to-end sum rate. However, the application of such methods is limited to environments wherein interference from other links and networks is not considered. Thus, it is difficult to apply them to practical multi-hop relay networks. In this paper, we propose a generalized version of the VMBT in which intra- and inter-network interferences are simultaneously caused by multiple transmission of clusters in the same network and each network’s usage of the same frequency band, respectively. To achieve this goal, we propose an effective interference nulling VMBT scheme. Simulation results show that the proposed scheme has efficient performance in terms of average end-to-end sum rate compared with conventional schemes.