Abstract
In this paper, we investigate the problem of wideband sensing for cognitive radio. Due to resource constraint, a cognitive node targets at finding a given number of spectrum holes, which is studied under a novel wideband sensing architecture. Specifically, the cognitive node can dynamically focus its sensing measurements on different portions of contiguous channels. An adaptive wideband sensing scheme is proposed under the standard Bayesian experimental design framework via three steps: (1) define a Bayesian cost that incorporates the numbers of desired spectrum holes, (2) design hypothesis testing rule to detect access opportunities, and (3) identify a scheme to adapt the measurements during the sensing process. In order to facilitate implementation, we further propose an approximated Bayesian experiment design scheme to reduce the computational complexity. The performance gain of our wideband sensing scheme is demonstrated via numerical simulation.
Highlights
Cognitive radio (CR) technique can opportunistically utilize channels that are not temporally unoccupied by primary users (PUs), and it provides an attractive solution to tackle the spectrum scarcity [1–3]
We study the WSS problem with the framework of Bayesian experimental design [11], which consists of two dimensions: one is how to make detection decision given the initial belief about channel’s occupancy and a sequence of observations taken over different portions of channels; the other is how to adaptively take measurements based on current belief about channel’s occupancy
In order to reduce the complexity of the standard Bayesian experimental design (BED), we introduce two approximations
Summary
Cognitive radio (CR) technique can opportunistically utilize channels that are not temporally unoccupied by primary users (PUs), and it provides an attractive solution to tackle the spectrum scarcity [1–3]. We study the WSS problem with the framework of Bayesian experimental design [11], which consists of two dimensions: one is how to make detection decision given the initial belief about channel’s occupancy and a sequence of observations taken over different portions of channels; the other is how to adaptively take measurements based on current belief about channel’s occupancy. These two processes boost each other with the total goal to detect the given number of access opportunities.
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