A Mode Identification Procedure for Software Defined Radio Terminals in Case of Superimposed Signals

In this work, a mode identification system for superimposed signals in the same band is presented. More precisely, a signal processing technique, namely the Wigner-Ville distribution, combined with non parametric (k-Nearest Neighbors and Parzen) and Neural Network classifiers is proposed for identifying the transmission modes in an indoor wireless environment. A reconfigurable terminal based on Software Defined Radio technology is considered aiming at the identification of the presence of two coexistent communication modes such as Bluetooth, based on Frequency Hopping Code Division Multiple Access, and IEEE WLAN 802.11b, based on Direct Sequence Code Division Multiple Access. Results in terms of error classification probability, expressed as relative error frequency, will be provided with a comparison among the classifiers.