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Modeling of Sensor Network Transceiver Considering the Electromagnetic Wave Propagation in IoT System

  • Journal of Knowledge Information Technology and Systems
  • Abbr : JKITS
  • 2020, 15(5), pp.599-604
  • DOI : 10.34163/jkits.2020.15.5.002
  • Publisher : Korea Knowledge Information Technology Society
  • Research Area : Interdisciplinary Studies > Interdisciplinary Research
  • Received : September 13, 2020
  • Accepted : October 13, 2020
  • Published : October 31, 2020

JANG SUNG JIN 1

1유한대학교

Accredited

ABSTRACT

Recently Sensor network technology is a core infrastructure of ubiquitous environment in advanced intelligent society where anyone can use the knowledge and service they want anytime, anywhere by detecting or storing, processing, and integrating the information of things or environment from a number of miniaturized wireless sensors. In this paper, we use MIMO channel emulator for channel modeling in real environment and conduct wireless channel characteristic modeling which has a great influence on sensor data communication performance. We will design sensor network transceiver considering distortion by surrounding environment through measurement of USN sensor node, channel modeling and processing, visualization and analysis of channel measurement data. Cell planning is performed in advance using the wireless design software (RF-vu) of iBwave before the actual measurement-related equipment arrangement. The purpose of this step is to investigate the environment of the selected test site and to predict the received field strength (RSSI) through RF-vu. By using RF-vu, antenna is established in the arrangement on scenario and each location received intensity is measured. By doing so, time and effort can be reduced when actual related facilities are arranged and accuracy of channel modeling can be increased through the predicted result. In this paper, channel characteristics reappearance using Channel Emulator equipment is a method of reproducing channel characteristics based on standard channel model, and the other is channel emulator based on data measured using measurement equipment. The channel model was generated and the channel characteristics were reproduced.

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