Can primary activity statistics in Cognitive Radio be estimated under imperfect spectrum sensing?

Owing to the opportunistic nature of the Dynamic Spectrum Access (DSA) paradigm based on the Cognitive Radio (CR) concept, the behaviour and performance of DSA/CR systems depend on the spectrum occupancy pattern of the primary system. DSA/CR systems can monitor periodically the occupancy state of licensed channels in order to gain statistical information on their occupancy patterns, and exploit this information in decision-making processes. Based on the outcomes of periodic spectrum sensing decisions, DSA/CR systems can make an estimation of the duration of the channel idle/busy periods and compute relevant statistics such as the minimum period duration, the moments (e.g., mean and variance) and the underlying distribution. However, the imperfect performance of spectrum sensing methods may lead to inaccuracies on the estimated statistics. In this context, this work carries out a detailed simulation-based study on the impact of imperfect spectrum sensing performance on the estimation of the primary activity statistics. The relative impact of various parameters is analysed and quantified, and guidelines to properly configure the spectrum sensing function of DSA/CR systems are provided. Moreover, several methods to overcome sensing errors are proposed and evaluated.