• Title/Summary/Keyword: Convolutional code.

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The Performance Analysis of Equalizer for Next Generation W-LAN with OFDM System (OFDM 방식의 차세대 무선 LAN 환경에서 등화기의 성능 분석)

  • Han, Kyung-Su;Youn, Hee-Sang
    • Journal of Advanced Navigation Technology
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    • v.6 no.1
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    • pp.44-51
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    • 2002
  • This paper describes the performance evaluation and analysis of an Orthogonal Frequency-Division Multiplexing (OFDM) system having the least Inter Symbol Interference (ISI) in a multi-path fading channel environment. Wireless Local Area Network (W-LAN) in accordance with IEEE 802.11a and IEEE 802.11b provides high-speed transmission to universities, businesses and other various places. In addition, service providers can offer a public W-LAN service on restricted areas such as a subway. The proliferation of W-LAN has led to greater W-LAN service demands, but problems are also on the rise in offering a good W-LAN service. In particular, urban areas with high radio wave interference and many buildings are vulnerable to deteriorated QoS including disconnected data and errors. For example, when high-speed data is transmitted in such areas, the relatively high frequency generates ISI between Access Points (AP) and Mobile Terminals (such as a notebook computer), leading to a frequency selective fading channel environment. Consequently, it is difficult to expect a goodW-LAN service. The simulation proves that the OFDM system enables W-LAN to implement QoS in high-speed data transmission in a multi-path fading channel environment. The enhanced OFDM performance with 52 sub-carriers is verified via data modulation methods such as BPSK, QPSK and 16QAM based on IEEE 802.11a and punched convolutional codes with code rate of 1/2 and 3/4 and constraint length of 7. Especially, the simulation finds that the OFDM system has better performance and there is no data disconnection even in a mobile environment by applying a single tap equalizer and a decision feedback equalizer to a mobile channel environment with heavy fading influence. Given the above result, the OFDM system is an ideal solution to guarantee QoS of the W-LAN service in a high-speed mobile environment.

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IoT Open-Source and AI based Automatic Door Lock Access Control Solution

  • Yoon, Sung Hoon;Lee, Kil Soo;Cha, Jae Sang;Mariappan, Vinayagam;Young, Ko Eun;Woo, Deok Gun;Kim, Jeong Uk
    • International Journal of Internet, Broadcasting and Communication
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    • v.12 no.2
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    • pp.8-14
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    • 2020
  • Recently, there was an increasing demand for an integrated access control system which is capable of user recognition, door control, and facility operations control for smart buildings automation. The market available door lock access control solutions need to be improved from the current level security of door locks operations where security is compromised when a password or digital keys are exposed to the strangers. At present, the access control system solution providers focusing on developing an automatic access control system using (RF) based technologies like bluetooth, WiFi, etc. All the existing automatic door access control technologies required an additional hardware interface and always vulnerable security threads. This paper proposes the user identification and authentication solution for automatic door lock control operations using camera based visible light communication (VLC) technology. This proposed approach use the cameras installed in building facility, user smart devices and IoT open source controller based LED light sensors installed in buildings infrastructure. The building facility installed IoT LED light sensors transmit the authorized user and facility information color grid code and the smart device camera decode the user informations and verify with stored user information then indicate the authentication status to the user and send authentication acknowledgement to facility door lock integrated camera to control the door lock operations. The camera based VLC receiver uses the artificial intelligence (AI) methods to decode VLC data to improve the VLC performance. This paper implements the testbed model using IoT open-source based LED light sensor with CCTV camera and user smartphone devices. The experiment results are verified with custom made convolutional neural network (CNN) based AI techniques for VLC deciding method on smart devices and PC based CCTV monitoring solutions. The archived experiment results confirm that proposed door access control solution is effective and robust for automatic door access control.