Abstract
Cooperative spectrum sensing exploits the spatial diversity to improve the detection of occupied channels in cognitive radio networks (CRNs). Cooperative compressive spectrum sensing (CCSS) utilizing the sparsity of channel occupancy further improves the efficiency by reducing the number of reports without degrading detection performance. In this paper, we firstly and mainly propose the referred multi-candidate orthogonal matrix matching pursuit (MOMMP) algorithms to efficiently and effectively detect occupied channels at fusion center (FC), where multi-candidate identification and orthogonal projection are utilized to respectively reduce the number of required iterations and improve the probability of exact identification. Secondly, two common but different approaches based on threshold and Gaussian distribution are introduced to realize the multi-candidate identification. Moreover, to improve the detection accuracy and energy efficiency, we propose the matrix construction based on shrinkage and gradient descent (MCSGD) algorithm to provide a deterministic filter coefficient matrix of low t-average coherence. Finally, several numerical simulations validate that our proposals provide satisfactory performance with higher probability of detection, lower probability of false alarm and less detection time.
Highlights
Cognitive radio (CR), as a promising technology to improve the spectrum efficiency in wireless communication, has drawn great attentions in recent years [1]
In multi-candidate orthogonal matrix matching pursuit (MOMMP) based on Gaussian distribution (MOMMP-GD) algorithm, an uncertain number of coordinates are identified in each iteration according to the distribution of energy of row vectors in identification matrix; 3.) We propose the matrix construction based on shrinkage and gradient descent (MCSGD) algorithm to construct a deterministic filter coefficient matrix, which is of low t-averaged coherence; 4.) The advantages of integrating MOMMP and MCSGD algorithms are higher probability of exactly detecting occupied channels, less detection time, and unnecessary transmission of the components of deterministic filter coefficient matrix
In this paper, we firstly proposed MOMMP algorithms to efficiently detect occupied channels in CR networks (CRNs), in which multi-candidate identification reduces the number of required iterations but does not degrade the detection accuracy
Summary
Cognitive radio (CR), as a promising technology to improve the spectrum efficiency in wireless communication, has drawn great attentions in recent years [1]. The main contributions of this paper can be stated as: 1.) We propose the MOMMP algorithms to reduce detection time without degrading detection accuracy, in which multi-candidate identification and orthogonal projection are respectively implemented in each iteration to detect several occupied channels and recover partial state data; 2.) We introduce two simple approaches to realize the multi-candidate identification.
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