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LPWS Algorithm for Wideband Spectrum Sensing

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Abstract

Wideband or multi-band spectrum sensing is an essential functionality for cognitive radio (CR) networks. It enables a secondary user to identify spectral holes dynamically and transmit opportunistically so as not to interfere with cohabiting primary users over the same bands. This paper presents an effective wideband spectrum sensing method based on linear programming (named as LPWS algorithm) for a 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, making use of \(l_{\infty }\)-norm, the sparse reconstruction problem is modelled 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, (1) it can reduce system overhead since single antenna is used instead of multiple antennas or sensing nodes. (2) The unknown noise variances can be eliminated effectively by a linear transformation. (3) It is computationally simpler since it is efficiently formulated in terms of the LP problem based on real-valued computation, etc. Simulation results are presented to verify the efficiency of the proposed method.

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Acknowledgments

This work has been supported by the Program for New Century Excellent Talents in University (NCET-13-0105), and by the Support Program for Hundreds of Outstanding Innovative Talents in Higher Education Institutions of Hebei Province, under Grant No. BR2-259, and by Natural Science Foundation of Hebei Province (No. F2016501139), and by the Specialized Research Fund for the Doctoral Program of Higher Education of China (No. 20130042110003), and by the Fundamental Research Funds for the Central Universities under Grant No. N142302001. The authors also gratefully acknowledge the helpful comments and suggestions of the reviewers, which have significantly improved the presentation of this paper.

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  1. Engineering Optimization and Smart Antenna Institute, Northeastern University at Qinhuangdao, Qinhuangdao, China

    Fulai Liu & Ruiyan Du

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  1. Fulai Liu
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  2. Ruiyan Du
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Correspondence to Fulai Liu or Ruiyan Du.

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Liu, F., Du, R. LPWS Algorithm for Wideband Spectrum Sensing. Wireless Pers Commun 91, 1259–1270 (2016). https://doi.org/10.1007/s11277-016-3526-z

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