Implementation of wavelet analysis for spectrum opportunity detection

Cognitive Radio (CR) introduces the idea of system awareness and intelligent adaptability in order to provide more efficient spectrum utilization especially in spectrum scarcity environment, which is happening in wireless communications. One of the key CR functionalities is the spectrum sensing, which allows CRs to monitor radio environment and detect unused spectrum. A fast and accurate detection approach is very vital since it provides interference avoidance to the existing users, which in many cases are licensed users. Much work has been undertaken to propose spectrum sensing techniques; however narrowband spectrum sensing is focused. In the case of high spectrum utilization, which increases spectrum scarcity, wideband spectrum sensing needs to be employed to provide better chance of detecting spectrum opportunity. In this paper, the application of wavelet transform technique for spectrum opportunity detection in cognitive radios is documented. Edge detection using wavelet analysis is employed for the wideband spectrum sensing. The paper presents research approach as well as system testing, which involves the development of the test platform used to obtain live spectrum sensing results. The implementation results prove the practicality of the approach as it provides fast and accurate spectrum opportunity detection.