An Effective Wideband Spectrum Sensing Method for a Single CR

Abstract

This paper presents a wideband spectrum sensing algorithm for a cognitive radio (CR) user equipped with a single receiving antenna. Firstly, the proposed method utilizes the temporal smoothing technique to form a virtual multi-antenna structure. Secondly, the wideband spectrum sensing problem is reformulated as a sparse reconstruction problem by exploiting a sparse representation of the virtual multi-antenna array covariance vector. Finally, the sparse reconstruction problem is modeled as a linear programming (LP) problem and hence can be solved efficiently. The presented method offers a number of advantages over other recently proposed methods. For examples, the unknown noise variances can be eliminated effectively by a linear transformation. It is computationally simpler since it is efficiently formulated in terms of the LP problem, etc. Simulation results are presented to verify the efficiency of the proposed method. Introduction For future CR networks, wideband or multi-band spectrum sensing is a crucial requirement for monitoring the primary users (PUs) activities and detecting spectrum holes for dynamic spectrum access, which can potentially improve spectrum utilization by allowing a secondary user (SU) or SUs to opportunistically utilize the spectrum if the primary user (PU) or PUs are inactive [1][2]. Various wideband spectrum sensing methods have been proposed in the literatures. For examples, ED is applied to wideband spectrum sensing problem [3]. A wavelet transform based method is proposed [4]. A simple approach to wideband spectrum sensing is presented [5]. Compressive sensing theory is applied in sense wideband spectrum [6]. A mixed-signal parallel segmented compressive sensing architecture is introduced for wideband spectrum sensing [7]. A distributed compressive sensing-based wideband sensing algorithm is presented for cooperative multihop CR networks [8]. Another framework of cooperative spectrum sensing is presented [9]. A multistage wiener filter (MSWF) based wideband spectrum sensing method is proposed [10]. In this paper, a new wideband spectrum sensing method is developed for a CR user equipped with a single receiving antenna. The proposed approach gives an effective sparse representation method by exploiting the virtual multi-antenna array covariance. Thus, all spectral holes can be effectively detected by finding the sparse coefficients. And then, the wideband spectrum sensing problem is modeled as a linear programming (LP) problem based on real-valued computation so that it can be solved efficiently. The outline of the paper is organized as follows. The data model is described in Section 2. Section 3 introduces the proposed LPWS algorithm. Section 4 shows some simulation results. Finally, the conclusion is given in Section 5.