Implementation of a real-time auto-tunable energy detector for spectrum sensing in the context of cognitive radio

Abstract

With the ever increasing popularity of wireless applications, more innovative ways of enhancing spectral efficiency are needed in-order to avail more bandwidth. One such way, is to allow for secondary use of channels allocated to a licensed primary user, but which in a given time or location happen to be idle. This is on condition, that no harmful radio interference is caused to the licensed primary user, and that the secondary user should vacate the channel immediately, once the former is present. One of the proposed technologies to enable this, is the Cognitive Radio (CR). A CR is a form of wireless communication in which a transceiver can intelligently detect which communication channels are in use and which are not, and instantly move into vacant channels while avoiding occupied ones. This is with an aim of optimizing the use of available radio-frequency (RF) spectrum while minimizing interference to other users. A key requirement of CR is spectrum sensing which aids in the detection of the channels status. Several spectrum sensing methods exist but the energy detection method is preferred due to its simplicity and ability to sense even unknown signals. Most of the research work carried out in this area is simulation based. Where practical implementation has been done, it involved sensing of only a narrow radio spectrum band. An implementation of a wide band auto- tunable energy detector would be more useful and realistic in the context of cognitive radio. This paper presents results of a practical real-time auto-tunable energy detector implemented in MATLAB, using the Universal Serial Radio Peripheral (USRP) N200 kit, that could perform spectrum sensing within the 10 MHz to 3.2 GHz spectrum band. The system was able to sense any desired radio band or channel within this range and detect the presence or absence of the licensed primary user signal. The performance of the implemented system was compared with that of a commercial spectrum analyzer using the probability of detection and the probability of false alarm parameters.The performances of the two systems were found to be very similar thus validating our system. Keywords—Cognitive Radio, Energy detector, Spectrum sensing, USRP.