Use of Time-frequency Analysis and Neural Networks for Mode Identification in a Software Radio Based Wireless Terminal for Ambient Intelligence Applications
نویسندگان
چکیده
In this work a preliminary study for identifying the transmission modes in a software radio (SR) based wireless terminal for ambient intelligence application is presented. In particular, the context is the identification of the presence of two communications mode as Bluetooth Personal Area Network (PAN) based on Frequency Hopping (FH) air interface, and IEEE WLAN 802.11b based on Direct Sequence Code Division Multiple Access (DS-CDMA). This mode identification procedure is performed employing time frequency analysis and neural networks. Results in terms of correct classification probability will be provided.
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تاریخ انتشار 2003