Abstract:

In the future heterogeneous wireless networks,since primary user (PU) and cognitive secondary user (SU) are not coordinated to be synchronous,it will result in sense timing difference between PU’s transmitter and SU’s receiver.For this asynchronous sense case,a new asynchronous sensing algorithm based on Bayesian estimation theory was proposed.A unified dynamic state space model was first proposed to describe the observable energy relationship with dynamic PU state and unknown timing difference.Then,an iterative estimation scheme was designed using stochastic finite set and the rules of maximum posterior probability.Finally,approximated estimation results were obtained by using a particle filter.The simulation results show that the proposed asynchronous scheme significantly eliminates the uncertainty of the received signal information and thus improves the spectrum sensing performance by obtaining the time difference accurately.

Key words: spectrum sensing, asynchronous perception, dynamic state-space model, maximum posterior probability,joint estimation