Wideband Spectrum Sensing by Model Order Selection

Abstract

Spectrum sensing is an essential functionality in cognitive radio (CR) systems allowing us to discover spectrum opportunities and enabling primary user (PU) protection. Wideband spectrum sensing (WS) improves the awareness of the surrounding radio environment by jointly monitoring multiple frequency bands. In this paper we propose a WS approach based on the observation of a frequency domain representation of the received signal and the adoption of model order selection (MOS) to identify the occupied frequency components. We provide a general formulation of the problem valid for any kind of spectral representation and then focus on the case in which discrete Fourier transform (DFT) is used. This choice is motivated by the fact that DFT blocks are available in many wireless systems, such as OFDM receivers and recently proposed software radio architectures. We provide analytical expressions for the maximum probability of correct selection of the occupied sub-bands valid for MOS approaches encompassed within the generalized information criterion (GIC). We then propose a method for designing the selection algorithm to balance overestimation and underestimation. Numerical results show that the MOS scheme derived for DFT can be successfully applied also when more accurate frequency representations, such as multitaper (MT) spectrum estimates, are adopted.