On Using Interference-Aware Spectrum Sensing for Dynamic Spectrum Access in Cognitive Radio Networks
Spectrum sensing is an important step toward enabling dynamic spectrum access in cognitive radio networks. To ensure that primary users are properly protected while maximizing the performance of secondary users, most related work considers the metrics of probabilities of missed detection and false alarm for determining optimal spectrum sensing parameters. In this paper, we argue that spectrum sensing based entirely on the two metrics is unable to maximize spectrum utilization for dynamic spectrum access. We show that, to meet the requirement of the probability of missed detection, conventional spectrum sensing techniques can unnecessarily increase the probability of false alarm in scenarios with good spectrum reuse opportunity, thus lowering the ability to leverage spectrum holes. To address this problem, we define the probability of interference and propose a new metric for spectrum sensing to consider both the probabilities of interference and missed detection. We first investigate the problem of optimal spectrum hole discovery for a single secondary user based on the proposed metric, and then extend to the problem of cooperative spectrum sensing among a group of secondary users. Compared against conventional sensing techniques presented in related work, we show through simulations that interference-aware spectrum sensing can potentially result in better utilization of the spectrum by allowing the secondary user to maximize its transmission opportunity without sacrificing the desired degree of protection for primary users.
spectrum detection cooperative sensing data and decision fusion dynamic programming