• Journal of KIISE:Information Networking
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• v.33 no.1
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• pp.91-102
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• 2006

We analyze the performance of MAC-layer Reed-Solomon error recovery in the cdma2000 1xEV-DO Broadcast and Multicast Services (BCMCSs) environment, with respect to the size of the ECB (Error Control Block) and the air-channel condition, and establish the relationship between ECB size, error recovery capacity and service latency. From this we propose an adaptive error recovery scheme which adjusts the size of the ECB to reflect the environment of the mobile nodes so as to meet the required service quality (target bit error-rate), while reducing the latency of real-time applications. Extensive simulation results show the effectiveness of our approach compared to the current static scheme. Proposed adaptive schemes achieves near optimal solution with respect to service latency while satisfying the required service quality.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.6 s.312
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• pp.110-116
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• 2006

In this paper, we implement a speech recognition system to support ubiquitous sensor network application services such as switch control, authentication, etc. using wireless audio sensors. The proposed system is consist of the wireless audio sensor, the speech recognition algorithm using psychoacoustic model and LDPC(low density parity check) for correcting errors. The proposed speech recognition system is inserted in a HOST PC to use the sensor energy effectively mil to improve the accuracy of speech recognition, a FEC(Forward Error Correction) system is used. Also, we optimized the simulation coefficient and test environment to effectively remove the wireless channel noises and correcting wireless channel errors. As a result, when the distance between sensor and the source of voice is less then 1.0m FAR and FRR are 0.126% and 7.5% respectively.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.6
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• pp.709-717
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• 2002

A new multi constant modulus algorithm (MCMA) for a blind decision feedback equalizer is proposed. In order to avoid the error propagation problem in the conventional DFE structure, Feed-Back Filter coefficients are updated only after Feed-Forward Filter coefficients are sufficiently converged to the steady state. Therefore, it has the problem of slow convergence speed characteristics. To overcome this drawback, the proposed MCMA algorithm uses not only new cost function considering the minimum distance between the received signal and the representative value containing the statistical characteristics of the transmitted signal, but also adaptive step-size according to the equalizer outputs to fast convergence speed of FBF. Simulations were carried out under the certified communication channel environment to evaluate a performance of the proposed equalizer. The simulation results show that the proposed equalizer has an improved convergence and SER performance compared with previous methods. The proposed techniques offer the possibility of practical equalization for cable modem and terrestrial HDTV broadcast (using 8-VSB or 64-QAM) applications.

• The Journal of the Korea Contents Association
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• v.7 no.2
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• pp.100-108
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• 2007

Currently, multimedia stream services are provided in various network environments such as wireless networks. It is crucial to address QoS problem for multimedia service in heterogeneous networks. This paper suggests the scheme to increase the efficiency for the transmission of multimedia data. We also propose the adaptive algorithm that switch between UDP and TCP based on the size of the transmitted multimedia data. In addition, it presents the method that duplicates the multimedia data for the efficiency of transmission. We designed the MPEG stream service and conducted the simulation to verify our adaptive MPEG stream service.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.334-337
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• 2010

디지털 선박 운행시 예기치 못한 상황에 의한 선박 내 화재나 충돌 등 긴급 상황 발생 시에 대형의 해난 사고가 발생할 수 있다. 이에 본 논문에서는 선박 상태를 자체 진단하여 모니터링하고 위험 분석을 통해 관리할 수 있는 시스템을 구현하고자 한다. 해양 디지털선박의 환경, 상황을 수집할 수 있는 무선 센서를 이용하여 수집된 환경 정보를 분석하는 시스템을 제안하였으며, 센싱된 데이터를 분석하기 위하여 역전파 신경망을 설계하였다. 300개의 데이터 집합을 사용하여 역전파 신경망을 실험한 결과 약 96%의 정확도를 가졌다. 제안된 시스템은 하드웨어 (UStar-2400 ISP, UStar-2400, Wireless sensors) 부분과 소프트웨어 부분(User Interface module)으로 구성되며 소프트웨어 부분은 HOST PC에 삽입된다. 그리고 시스템의 정확도를 개선하기 위하여 전방향 에러 정정 시스템(LDPC)을 구현하였고 진단된 결과는 CDMA 방식으로 전송하여 해양디지털선박 감지 모니터링 시스템을 구현했다.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.4 s.316
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• pp.36-44
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• 2007

In this paper, we implement the speech & face recognition system to support various ubiquitous sensor network application services such as switch control, authentication, etc. using wireless audio and image interface. The proposed system is consist of the H/W with audio and image sensor and S/W such as speech recognition algorithm using psychoacoustic model, face recognition algorithm using PCA (Principal Components Analysis) and LDPC (Low Density Parity Check). The proposed speech and face recognition systems are inserted in a HOST PC to use the sensor energy effectively. And improve the accuracy of speech and face recognition, we implement a FEC (Forward Error Correction) system Also, we optimized the simulation coefficient and test environment to effectively remove the wireless channel noises and correcting wireless channel errors. As a result, when the distance that between audio sensor and the source of voice is less then 1.5m FAR and FRR are 0.126% and 7.5% respectively. The face recognition algorithm step is limited 2 times, GAR and FAR are 98.5% and 0.036%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.5
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• pp.1008-1013
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• 2009

In this paper, we proposed the biological signal (body heat, pulse, breathe rate, and blood pressure) analysis system using wireless sensor. In order to analyze, we designed a back-propagation neural network system using expert group system. The proposed system is consist of hardware patt such as UStar-2400 ISP and Wireless sensor and software part such as Knowledge Base module, Inference Engine module and User Interface module which is inserted in Host PC. To improve the accuracy of the system, we implement a FEC (Forward Error Correction) block. For conducting simulation, we chose 100 data sets from Knowledge Base module to train the neural network. As a result, we obtained about 95% accuracy using 128 data sets from Knowledge Base module and acquired about 85% accuracy which experiments 13 students using wireless sensor.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.6B
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• pp.859-866
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• 2010

Digital vessels can occur large a disaster at sea because vessels in fire and collision in case of certain unforeseen circumstances. In this paper, We propose digital vessel context monitoring system through risk analysis. We propose environment information analysis system using wireless sensor that have to acquire marine environment and context of marine digital vessel. For conducting simulation, we chose 300 data sets to train the neural network. As a result, we obtained about 96% accuracy for fire risk context and we obtained 88.7% accuracy for body of vessel risk context. To improve the accuracy of the system, we implement a FEC (Forward Error Correction) block. We implemented digital vessel context monitoring system that transmitted to diagnosis result in CDMA.