• ETRI Journal
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• v.35 no.5
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• pp.786-796
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• 2013

In this paper, we propose a hybrid time-division multiplexing and dense wavelength-division multiplexing scheme to implement a cost-effective and scalable long-reach optical access network (LR-OAN). Our main objectives are to increase fiber plant utilization, handle upstream and downstream flow through the same input/output port, extend the reach, and increase the splitting ratio. To this end, we propose the use of an arrayed waveguide grating (AWG) and an erbium-doped fiber amplifier (EDFA) in one configuration. AWG is employed to achieve the first and second objectives, while EDFA is used to achieve the third and fourth objectives. The performance of the proposed LR-OAN is verified using the Optisystem and Matlab software packages under bit error rate constraints and two different approaches (multifiber and single-fiber). Although the single-fiber approach offers a more cost-effective solution because service is provided to each zone via a common fiber, it imposes additional losses, which leads to a reduction in the length of the feeder fiber from 20 km to 10 km.

• Journal of Korea Multimedia Society
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• v.23 no.10
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• pp.1236-1249
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• 2020

In a most recent object tracking research work, applying Convolutional Neural Network and Recurrent Neural Network-based strategies become relevant for resolving the noticeable challenges in it, like, occlusion, motion, object, and camera viewpoint variations, changing several targets, lighting variations. In this paper, the LSTM Network-based Tracking association method has proposed where the technique capable of real-time multi-object tracking by creating one of the useful LSTM networks that associated with tracking, which supports the long term tracking along with solving challenges. The LSTM network is a different neural network defined in Keras as a sequence of layers, where the Sequential classes would be a container for these layers. This purposing network structure builds with the integration of tracking association on Keras neural-network library. The tracking process has been associated with the LSTM Network feature learning output and obtained outstanding real-time detection and tracking performance. In this work, the main focus was learning trackable objects locations, appearance, and motion details, then predicting the feature location of objects on boxes according to their initial position. The performance of the joint object tracking system has shown that the LSTM network is more powerful and capable of working on a real-time multi-object tracking process.

• Journal of Digital Convergence
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• v.10 no.8
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• pp.225-231
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• 2012

In this paper, we implement a wireless home monitoring system using physical computing platform with the open source type for house environment management. Sensors for temperature, optics and ultrasonic waves are used for home environment elements detection and control for the home safety. To obtain information related with home and transmit it to RIA Windows server system, XBee wireless communication system is used and the transmitted information is saved in mySQL database for history management. The possibility of prevention against fire disaster of a house situated in a dense buildings area and highly populated environments is suggested by adopting the proposed system.

• ETRI Journal
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• v.30 no.2
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• pp.261-267
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• 2008

In this paper, we propose and demonstrate a cost-effective technique to upgrade the capacity of dense wavelength division multiplexing (DWDM) networks to a 40 Gb/s line rate using the existing 10 Gb/s-based infrastructure. To accommodate 40 Gb/s over the link optimized for 10 Gb/s, we propose applying a combination of super-FEC, carrier-suppressed return-to-zero, and pre-emphasis to the 40 Gb/s transponder. The transmission of 40 Gb/s DWDM channels over existing 10 Gb/s line-rate long-haul DWDM links, including $40{\times}40$ Gb/s transmission over KT's standard single-mode fiber optimized for 10 Gb/s achieves successful results. The proposed upgrading technique allows the Q-value margin for a 40 Gb/s line rate to be compatible with that of 10 Gb/s.

• Journal of information and communication convergence engineering
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• v.18 no.3
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• pp.155-161
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• 2020

The fifth generation (5G) is a state-of-the-art mobile communication access technology that uses sub 6 GHz bands and mmWave. Presently, the 5G network is partially deployed along with 4G in areas with dense traffic. In the future, the demand for the 5G bandwidth may increase. Thus, it is necessary to study the coexistence between the 5G and radio systems using adjacent or same channels to eliminate the interference between radio systems and efficiently utilize the frequency. This paper analyzed the impact of 5G new radio downlink on the fixed-satellite service earth station operating at the co-channel and adjacent channel in the upper 3.7 GHz band using the Spectrum Engineering Advanced Monte Carlo Analysis Tool, which is based on the Monte Carlo method. The results of this paper can be utilized for planning the frequency allocation of 5G networks; they can also be used as a guideline for deploying 5G base stations around a fixed-satellite service earth station.

• ETRI Journal
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• v.38 no.2
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• pp.314-325
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• 2016

This paper examines the resource gain that can be obtained from the creation of clusters of nodes in densely populated areas. A single node within each such cluster is designated as a "hotspot"; all other nodes then communicate with a destination node, such as a base station, through such hotspots. We propose a semi-distributed algorithm, referred to as coordinated cognitive tethering (CCT), which clusters all nodes and coordinates hotspots to tether over locally available white spaces. CCT performs the following these steps: (a) groups nodes based on a modified k-means clustering algorithm; (b) assigns white-space spectrum to each cluster based on a distributed graph-coloring approach to maximize spectrum reuse, and (c) allocates physical-layer resources to individual users based on local channel information. Unlike small cells (for example, femtocells and WiFi), this approach does not require any additions to existing infrastructure. In addition to providing parallel service to more users than conventional direct communication in cellular networks, simulation results show that CCT can increase the average battery life of devices by 30%, on average.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4703-4723
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• 2018

In recent years, dense small cell network has been deployed to address the challenge that has resulted from the unprecendented growth of mobile data traffic and users. It has proven to be a cost efficeient solution to offload traffic from macro-cells. Software defined heterogeneous wireless network can decouple the control plane from the data plane. The control signal goes through the macro-cell while the data traffic can be offloaded by small cells. In this paper, we propose a framework for cell virtualization and user association in order to satisfy versatile requirements of multiple tenants. In the proposed framework, we propose an interference graph partioning based virtual-cell association and customized physical-cell association for multi-homed users in a software defined small cell network. The proposed user association scheme includes 3 steps: initialization, virtual-cell association and physical-cell association. Simulation results show that the proposed virtual-cell association outperforms the other schemes. For physical-cell association, the results on resource utilization and user fairness are examined for mobile users and infrastructure providers.

• Smart Structures and Systems
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• v.17 no.4
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• pp.669-690
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• 2016

Advances in sensor technologies have led to the instrumentation of sensor networks for bridge monitoring and management. For a dense sensor network, enormous amount of sensor data are collected. The data need to be managed, processed, and interpreted. Data management issues are of prime importance for a bridge management system. This paper describes a data management infrastructure for bridge monitoring applications. Specifically, NoSQL database systems such as MongoDB and Apache Cassandra are employed to handle time-series data as well the unstructured bridge information model data. Standard XML-based modeling languages such as OpenBrIM and SensorML are adopted to manage semantically meaningful data and to support interoperability. Data interoperability and integration among different components of a bridge monitoring system that includes on-site computers, a central server, local computing platforms, and mobile devices are illustrated. The data management framework is demonstrated using the data collected from the wireless sensor network installed on the Telegraph Road Bridge, Monroe, MI.

• Convergence Security Journal
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• v.13 no.6
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• pp.3-9
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• 2013

With the rapidly changing information communication environment and development of technologies, the informati on networks are evolved from traditional fixed form to an active variable network that flexible large variety of data can be transferred. To reflect the needs of users, the next generation using DWDM (Dense Wavelength Division M ultiplexing) transmission system and OXC (Optical Cross Connect) form a dynamic network. After that GMPLS (Ge neralized Multi-Protocol Label Switching) can be introduced to dynamically manage and control the Reconfigurable Optical Add-drop Multiplexer (ROADM)/Photonic Cross Connect (PXC) based network. This paper propose a softw are architecture of Path Computation Element (PCE) protocol that has proposed by Internet Engineering Task Force (IETF) to path computation. The functional blocks and Application Programming Interface (API) of the PCE protoco l implementation are also presented.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.1C
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• pp.113-119
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• 2009

The training sequence with the appropriate length for equalization and initial synchronization is necessary before sending the pure data in the burst transmission type DS-UWB system. The length of the training sequence is one of the factors which make throughput decreased. The noble structure with the variable length of the training sequence whose length can be adaptively tailored according to the channel conditions (CM1,CM2,CM3,CM4) in the DS-USB systems is proposed. This structure can increase the throughput without sacrificing the performance than the method with fixed length of training sequence considering the worst case channel conditions. Simulation results under IEEE 802.15.3a channel model show that the proposed scheme can achieve higher throughput than a conventional one with the slight loss of BER performance. And this structure can reduce the computation complexity and power consumption with selecting the short length of the training sequence.