Recent Advances on Wideband Spectrum Sensing for Cognitive Radio

Spectrum sensing plays a fundamental role in cognitive radio (CR) networks allowing to discover spectrum opportunities and enabling primary user (PU) protection. However, it represents also one of its most challenging aspects due to the requirement of performing radio environment analysis in a short observation time and the fact that its performance can be strongly affected by harsh channel conditions and lack of knowledge about the PU characteristics. In literature, many techniques have been proposed, starting from the most popular algorithms, such as energy detection, to the most advanced, such as, e.g., eigenvalue based detection and cooperative approaches. Most of these techniques have been conceived to assess the occupancy of PUs within a single frequency band. A better knowledge of the surrounding radio environment can be reached exploiting wideband spectrum sensing, that consists in a joint observation of multiple bands and joint detection on the occupancy of each sub-band. Recently, different wideband approaches have been proposed, mainly derived from advanced spectral analysis techniques such as multitaper methods and compressive sensing. In this chapter, we propose a novel methodology for wideband spectrum sensing based on the computation of a frequency domain representation of the received samples and the use of information theoretic criteria (ITC) to identify which frequency components contain PU signals. This technique does not require the setting of a decision threshold, a problem for many spectrum sensing algorithms due to dependence on unknown parameters or difficulties in the statistical description of the decision metrics. 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 simplicity of implementation and the fact that DFT blocks are already available in many wireless systems, such as OFDM receivers. This wideband spectrum sensing approach can be adopted by a single CR node in a standalone manner or within a cooperative sensing scheme. Numerical results show that the algorithm derived for DFT can be also applied as an approximated approach when more accurate frequency representations, such as multitaper method (MTM) spectrum estimates, are adopted. Wideband ITC based sensing can be applied in scenarios in which approaches that require a high level of sparsity of the received signal (such as compressive sensing) can not be adopted.