A mode identification system for a reconfigurable terminal using Wigner distribution and non-parametric classifiers

In this work, a mode identification system for superimposed signals in the same band is presented. More precisely, a pattern recognition approach, based on the Wigner distribution for features extraction and non parametric classifiers (k-nearest neighbors and Parzen) is proposed for identifying the transmission modes in an indoor wireless environment. A reconfigurable terminal, based on software defined radio technology, is considered aimed at the identification of the presence of two co-existent 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, are provided with a comparison between the use of the two classifiers.