Fast and robust identification of GSM and LTE signals

Signal identification algorithms have found many applications in both military and commercial communications, such as spectrum surveillance, and software-defined and cognitive radios. Such algorithms are essential for building instruments used in radio spectrum monitoring. In this paper, we present an algorithm to identify signals from global system for mobile communications (GSM) and long-term evolution (LTE) networks. The presented algorithm relies on the signal cumulative distribution function as an identification feature, and on the Kolmogorov-Smirnov test as the decision criteria. The performance of the identification algorithm is evaluated using standard cellular signals generated and acquired using test and measurement equipment. Experimental results verify the applicability of the algorithm with short observation intervals leading to improved response time of the instrument. Moreover, the presented algorithm does not require timing and frequency offset estimation and correction; therefore, it has low implementation complexity.