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http://dx.doi.org/10.7471/ikeee.2021.25.2.252

Identification of Wi-Fi and Bluetooth Signals at the Same Frequency using Software Defined Radio  

Do, Van An (Dept. of Information & Communication Eng., Kongju National University)
Rana, Biswarup (Smart Natural Space Research Centre, Kongju National University)
Hong, Ic-Pyo (Dept. of Information & Communication Eng., Kongju National University)
Publication Information
Journal of IKEEE / v.25, no.2, 2021 , pp. 252-260 More about this Journal
Abstract
In this paper, a method of using Software Defined Radio (SDR) is proposed for improving the accuracy of identifying two kinds of signals as Wireless Fidelity (Wi-Fi) signal and Bluetooth signal at the same frequency band of 2.4 GHz based on the time-domain signal characteristic. An SDR device was set up for collecting transmitting signals from Wi-Fi access points (Wi-Fi) and mobile phones (Bluetooth). Different characteristics between Wi-Fi and Bluetooth signals were extracted from the measured result. The SDR device is programmed with a Wi-Fi and Bluetooth detection algorithm and a collision detection algorithm to detect and verify the Wi-Fi and Bluetooth signals based on collected IQ data. These methods are necessary for some applications like wireless communication optimization, Wi-Fi fingerprint localization, which helps to avoid interference and collision between two kinds of signals.
Keywords
Wi-Fi; Bluetooth; Signal Identification; Software Defined Radio; Time Domain;
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