Experimental Spectrum Sensing Measurements using USRP Software Radio Platform and GNU-Radio

In cognitive radio, the secondary users are able to sense the spectral environment and use this information to opportunistically access the licensed spectrum in the absence of the primary users. In this paper, we present an experimental study that evaluates the performance of two different spectrum sensing techniques to detect primary user signals in real environment. The considered spectrum sensing techniques are: sequential energy and cyclosationary feature based detectors. An Universal Software Radio Peripheral platform with GNU-Radio is employed for implementation purpose. We analyzed the performances of both spectrum sensing methods by measuring the detection probabilities as a function of SNR for a given false alarm probability. As predicted theoretically, experimental measurements show that the cyclostationnary feature detector performs better than the sequential energy detector. However sequential energy detector can be used for reduction of sensing time in the presence of strong signals.