LDLT Decomposition Based Spectrum Sensing in Cognitive Radio Using Hard Decision Criterion

Abstract

Inspired by random matrix theory, a quantity of eigenvalue based cooperative spectrum sensing methods have been proposed. The results are based on the asymptotical assumptions in need of large numbers of users and samples, which result in inferior performance with a few users. In this paper, sensing methods based on maximum eigenvalue and minimum eigenvalue of LDLT decomposition are proposed respectively with a view to improve the accuracy of decision threshold by means of hard decision criterion. The corresponding expressions of false alarm probability are also derived. Finally, both theoretical analyses and simulations demonstrate that the proposed two methods perform better than the existing eigenvalue based sensing methods for accurate decision threshold.