Temporal Entropy and Cognitive Information Based Efficient Environment Awareness Techniques in Cognitive Radio Networks

To efficiently utilize the vacant spectrum resources, different environment awareness techniques, such as the spectrum sensing, have been applied in cognitive radio networks (CRNs). However, the existing research works ignore the effects and differences between the long term and short term vacant spectrum quality of primary users. Therefore, the cognitive information sequence (CIS) concept has been proposed in this paper to represent the information sequence of the environment awareness results. Besides, the temporal entropy is proposed to reveal the uncertainty of CIS and the cognitive information is used to measure the uncertainty of the internal and external states of primary user (PU) that can be removed by the secondary user (SU). Moreover, the information theory techniques are applied to analyze the mathematical properties of temporal entropy and cognitive information in CIS. By utilizing the temporal entropy values which reveal the vacant spectrum quality, the optimal solutions for the efficient spectrum sensing techniques are proposed and verified by numerous results, such as the optimal period of spectrum sensing and the threshold of energy detector.