Uwb Network Recognition Based On Impulsiveness Of Energy Profiles

Two important functionalities in cognitive networking are network detection and recognition. Previous investigations showed that MAC sub-layer technology-specific features may offer a simple and direct way of performing such tasks; in particular, they allow to by-pass complex physical layer feature extraction based on a simple energy detection scheme, capable of producing a time-varying profile reflecting the presence vs. absence of packets over the air interface. Beyond summarizing previous experimental evidence that confirmed the validity of the approach for technologies in the ISM band, the purpose of this work is to investigate the possibility of extending the network recognition concept to underlay networks such as Ultra Wide Band. Preliminary results of experiments on UWB signals indicate that short-term energy profiles may highlight the peculiar impulsive characteristic of IEEE 802.15.4a-like signals. Continuous vs. impulsive signals may be correctly classified based on a simple but relevant feature such as short-term energy statistics. Moreover, short-term energy statistical features, as a function of increased window window duration, seem to highlight a multi-static vs. continuous behavior for impulse vs. continuous-wave radio transmissions.