Random sets theory based multi-dimensional spectrum sensing with multiple primary users

Multiple primary user signal detection in cognitive mobile network is one of the main cognitive radio problems. This paper introduces random sets theory into the process of mobile network cognitive spectrum sensing, and builds the motion model and the sensor model of multiple primary users, and uses Particle Probability Hypothesis Density Filter to realize real-time detection of the primary users, including the number and status (position, velocity, frequency, signal reception angle) of each primary user. Compared with traditional spectrum sensing methods, the proposed method can track the number of primary users, the position, frequency, as well as arrival of angle. Simulation results show that the random set theory for multidimensional cognitive mobile network can be realized on real-time detection and update of the state of each primary user. It can reliably and effectively detect the number and status of primary users with high capacity of resisting disturbance.