Demodulation-free protocol identification in heterogeneous wireless networks

Nowadays various wireless network protocols play respective roles to fulfill different demands. To better adapt to this heterogeneity and coexistence situation, it is critical for nodes to identify the available networks with high accuracy and low cost. Unlike traditional demodulation-based identification method, which is expensive and complexing, in this paper, we propose a novel conception called demodulation-free protocol identification. This method only employs the features of physical layer samples. We first extract features that can be used to identify different protocols. Specifically, a sparse sequence based Precision-Stable Folding Algorithm (PSFA) is proposed to detect periodicity feature, which is common in wireless network protocols. Then we construct a prototype with USRP to identify three commonly used protocols in the 2.4 GHz ISM band. Experiment results show that under low or moderate channel utilization, the accuracy is above 90%. We also show that the computational complexity is polynomial.