Efficient Wireless Microphone sensing: Subband energy detector principle and measured performance

Abstract

Spectrum scarcity has become a critical concern in wireless communication systems due to the limited availability of frequency spectrum. Hence, cognitive radio (CR) has been introduced as a solution for more effective use of the spectrum resources. Spectrum sensing (SS) is one of the key elements in the implementation of effective and reliable CR systems. Energy detection (ED) based SS is the most common sensing algorithm due to its low complexity. The main drawback of ED based SS is that it is highly dependent on the precise knowledge of the receiver noise variance. Hence, the performance of the ED algorithm is degraded significantly, when there is noise uncertainty in the estimation of the noise variance. In this study, we apply a recently proposed enhanced ED based algorithm to the sensing of Wireless Microphone (WM) signals, demonstrating robustness to noise uncertainty in real-time testing with actual WM signals. This so-called Max-Min ED algorithm is based on subband division of a wideband signal using an analysis filter bank (AFB) and utilizing the difference of maximum and minimum subband energies as the test statistic. Following the introduction of analytical models and scenarios of ED based SS algorithms, the sensing algorithms are implemented and tested using National Instruments (NI) Universal Software Radio Peripheral (USRP) and the NI-LabVIEW software platform, together with the necessary toolboxes.