• Journal of the Institute of Electronics Engineers of Korea TC
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• v.39 no.4
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• pp.165-172
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• 2002

In the next generation mobile communications, powerful channel coding is essential in order to obtain high quality multimedia services. Turbo code can achieve good error performance by iterative decoding, but more iterations result in additional computational complexity and delay. Thus, a method to reduce the number of iterations without additional performance degradation is needed. Turbo code with CRC is known to be the most efficient method to reduce the number of iterations. In this scheme, the performance may be degraded by the edge-effect like the conventional turbo code without CRC. In this paper, a method to eliminate the edge-effect is proposed by adopting D-parameter to the conventional s-random interleaver. As results of simulation, the edge-effect of the turbo code with CRC is shown to be successfully eliminated by using the new interleaver designed with D-parameter.

• The KIPS Transactions:PartB
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• v.13B no.5 s.108
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• pp.561-568
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• 2006

WPS(Wearable Personal Station) for next generation PC can define as a core terminal of 'Ubiquitous Computing' that include information processing and network function and overcome spatial limitation in acquisition of new information. As a way to acquire significant dynamic gesture data of user from haptic devices, traditional gesture recognizer based on desktop-PC using wire communication module has several restrictions such as conditionality on space, complexity between transmission mediums(cable elements), limitation of motion and incommodiousness on use. Accordingly, in this paper, in order to overcome these problems, we implement hand gesture recognition system using fuzzy algorithm and neural network for Post PC(the embedded-ubiquitous environment using blue-tooth module and WPS). Also, we propose most efficient and reasonable hand gesture recognition interface for Post PC through evaluation and analysis of performance about each gesture recognition system. The proposed gesture recognition system consists of three modules: 1) gesture input module that processes motion of dynamic hand to input data 2) Relational Database Management System(hereafter, RDBMS) module to segment significant gestures from input data and 3) 2 each different recognition modulo: fuzzy max-min and neural network recognition module to recognize significant gesture of continuous / dynamic gestures. Experimental result shows the average recognition rate of 98.8% in fuzzy min-nin module and 96.7% in neural network recognition module about significantly dynamic gestures.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.4B
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• pp.677-686
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• 2010

In this paper, we propose the virtual interface management scheme on the multi-mode mobile node for supporting multiple connections to various access networks in fixed mobile convergence (FMC) networks. The proposed scheme supports the virtualization of multiple physical network interfaces by presenting only the virtual interface to beyond IP layers and hiding physical network interfaces from them. In the proposed scheme, only one IP address is allocated to virtual interface without any IP allocations to physical network interfaces. Therefore, the proposed scheme does not change its IP address and keep it during the vertical handover, so that it can support the seamless handover of real-time multimedia services among heterogeneous access networks. The proposed scheme is implemented on the multi-mode mobile node with multiple network interfaces by using NDIS (Network Driver Interface Specifications) libraries. Through the mobility test-bed and the test application of virtual interface, we evaluate and analyze the performance of the proposed scheme.

• Journal of IKEEE
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• v.25 no.1
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• pp.156-167
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• 2021

In this paper, we propose a digital transceiver unit design for in-building of 5G optical repeaters that extends the coverage of 5G mobile communication network services and connects to a stable wireless network in a building. The digital transceiver unit for driving the proposed 5G optical repeater is composed of 4 blocks: a signal processing unit, an RF transceiver unit, an optical input/output unit, and a clock generation unit. The signal processing unit plays an important role, such as a combination of a basic operation of the CPRI interface, a 4-channel antenna signal, and response to external control commands. It also transmits and receives high-quality IQ data through the JESD204B interface. CFR and DPD blocks operate to protect the power amplifier. The RF transmitter/receiver converts the RF signal received from the antenna to AD, is transmitted to the signal processing unit through the JESD204B interface, and DA converts the digital signal transmitted from the signal processing unit to the JESD204B interface and transmits the RF signal to the antenna. The optical input/output unit converts an electric signal into an optical signal and transmits it, and converts the optical signal into an electric signal and receives it. The clock generator suppresses jitter of the synchronous clock supplied from the CPRI interface of the optical input/output unit, and supplies a stable synchronous clock to the signal processing unit and the RF transceiver. Before CPRI connection, a local clock is supplied to operate in a CPRI connection ready state. XCZU9CG-2FFVC900I of Xilinx's MPSoC series was used to evaluate the accuracy of the digital transceiver unit for driving the 5G optical repeater proposed in this paper, and Vivado 2018.3 was used as the design tool. The 5G optical repeater digital transceiver unit proposed in this paper converts the 5G RF signal input to the ADC into digital and transmits it to the JIG through CPRI and outputs the downlink data signal received from the JIG through the CPRI to the DAC. And evaluated the performance. The experimental results showed that flatness, Return Loss, Channel Power, ACLR, EVM, Frequency Error, etc. exceeded the target set value.