Abstract
In this paper, we present a novel hybrid framework combining compressive spectrum sensing with geo-location database to find spectrum holes in a decentralized cognitive radio. In the hybrid framework, a geo-location database algorithm is proposed to be stored locally at secondary users (SUs) to remove the extra transmission link to a centralized remote geo-location database. Specifically, by utilizing the output of the locally stored geo-location database algorithm, a data-assisted noniteratively reweighted least squares (DNRLS)-based compressive spectrum sensing algorithm is proposed to improve detection performance under sub-Nyquist sampling rates for wideband spectrum sensing, and to reduce the computational complexity of signal recovery. In addition, an efficient method for the calculation of maximum allowable equivalent isotropic radiated power in TV white space (TVWS) is also designed to further support SUs. The convergence and complexity of the proposed DNRLS algorithm are analyzed theoretically. Furthermore, the proposed framework is pioneered on real-time “from air” signals and data after having been validated by simulated signals and data in TVWS.
Highlights
W ITH the rapid development of wireless communications, the scarcity of spectrum resources becomes an urgent problem
After the proposed data-assisted non-iteratively reweighted least squares (DNRLS) compressive spectrum sensing algorithm is validated by the simulated signals and data, the proposed framework is tested on real-time signals collected by the CRFS RFeye node and the real data provided by the geo-location database from Nominet qualified by Ofcom
A stand-alone hybrid framework combining compressive spectrum sensing and geo-location database was designed for wideband spectrum in this paper
Summary
W ITH the rapid development of wireless communications, the scarcity of spectrum resources becomes an urgent problem. Motivated by the challenges identified above, the main contributions of this paper are listed as follows: 1) A hybrid framework combining compressive spectrum sensing with geo-location database is proposed in which a geo-location database algorithm is implemented at SUs locally to provide prior information for the compressive spectrum sensing. 3) In addition, an efficient approach for calculating the maximum allowable EIRP is proposed to further improve the accuracy and efficiency of the geo-location database algorithm stored at SUs. 4) based on the recent work on the trail within the Ofcom TVWS pilot [34], the proposed framework and algorithms are tested on real-time signals and data recorded by the CRFS RFeye node [35] and the regulator qualified geo-location database from Nominet [36] after having been validated by the simulated signals and data.
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