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

Abstract

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.

Identification of Communication Signals Using Learning Approaches for Cognitive Radio Applications

“…Overall, the results shown in Fig. 11 indicate the proposed approach has a detection performance that is similar to other cyclostationary detectors, such as those utilized in other works [53], [54].…”

“…It is noted that the signal characterization, such as the extraction of the PU signal frequency and bandwidth, offered by the proposed approach is a challenge for the conventional energy detector. It is seen from the results that the performance of the utilized energy detector is not the same as those presented in other papers [53], [54]. We attribute this variability to two factors: differences in the analysis parameters and differences in the actual SNRs of the signal.…”

Real-time adaptive spectrum sensing for cyclostationary and energy detectors

“…Similar flexibility coupled with processing speed can be achieved using field-programmable gate array (FPGA) platforms, which is why they have also been used for spectrum sensing applications in the recent years [12]- [16]. Several USRP-based implementations of energy and cyclostationary detectors as reported in [4]- [9] examine the scenario where one USRP is the PU transmitter, while the other is the SU receiver, which implements the spectrum sensing function.…”

“…The proposed detector is blind, in the sense, that it does not require any prior information about the signal, neither were the P d and P fa determined analytically, which makes the detector less flexible for introducing adaptability into it. In [9], the same cyclostationarity method was proposed and compared to a modified ED method, which compared the energy of sequential chunks of the gathered samples until above the upper boundary of a threshold, or below the lower boundary. This approach can improve the speed of the ED, however the method did not consider a fading scenario.…”

“…Although the cyclostationary detector requires much greater computational complexity than the ED, its advantage is that as the noise does not exhibit cyclostationary properties, the signal could be detected even if it is very weak. Results from various research studies ( [7], [8], [9] [36], [37], [38]) have shown that the method has very good detection accuracy in low SNR (the range −20 to 0 dB is of particular interest). In many of them, the SCF is compared against the decision threshold λ, however, in our implementation we use the CAF.…”