Interference Temperature Estimation Based on the Detection and Estimation of Angles of Arrival of Multiple Wide-Band Sources in Cognitive Radio Sensor Networks

Majority of evaluation methods on interference temperature algorithms are based on the assumption that either the interference signals or the user's signals are no directions. This is a mathematical constraint that is not satisfied in many applications. In fact, without consideration the signal directions increase estimation interference temperature, that is, reduce the frequency utilizing chance for users. In this paper, we consider situations where the interference signals and user's signals have directions in cognitive radio sensor networks. We propose an algorithm that estimates the interference temperature of this model using a generalization of the DOA (direction of arrival) algorithm. From this, we find the interference temperature and show that it does become smaller. We compare our method to the conventional (without considering directions) algorithm. The simulation studies show that the new method outperforms the conventional algorithm by reducing the estimation interference temperature and improving the frequency spectrum efficiency.