Performance Analysis And Optimization In Full-Duplex Cognitive Radio Systems With Non-Slotted Primary User State Change

With the rapid development of wireless communication networks,the available spectrum resources have become increasingly scarce.C ognitive radio(CR)technology has emerged to alleviate the shortage problem of spectrum resources.At the same time,full-duplex(FD)technology allows bi-directional communication to operate in the same frequency band,which can utilize the spectrum more efficiently.Therefore,the resear-ch of FD CR system has received extensive attention around the world.Finally,the study of spectrum states has been proved that it can make CR technology operate more precisely.Compared to slotted primary state(SPS)assumption,non-slotted primary state(NSPS)assumption has been proved to be a more general and accurate assumption to model the state of primary user(PU).Therefore,this paper will make capacity analysis and maximization in FD CR sy-stem with NSPS assumption to improve the spectral efficiency.The fir-st scenario is based on one PU spectrum band and single secondary user with full-duplex capability.The sensing probabilities are derived in case of non-slotted PU state.Then,slot duration,transmit power and two detection thresholds,respectively corresponding to two cases that secondary user(SU)is silent or active,are jointly optimized to maximize SU's capacity.Numerical results show that the proposed algorithm can achieve the near-optimal solution with a low computational complexity and a considerably higher capacity,compared to the ideal assumption of SPS.Further,this paper considers the resource allocation problem in FD CR system.Thus,the second scenario is based on a network,including multiple PU spectrum bands,a central base station with full-duplex capability and multiple SUs.In this paper,the spectral efficiency optimization problem is divided into two sub-optimization problems,which is CR parameters optimization and pair matching between spectrum bands and SUs.The sub-optimization algorithm is designed for two sub-optimization problems,and an alternating iteration algorithm is used to jointly optimize the problem.Simulation results verified that each sub-optimization algorithm has a positive contribution for the entire optimization problem.At the same time,the full-duplex CR system with NSPS assumption can always achieve a higher capacity compared to the half-duplex CR system with NSPS assumption and the full-duplex CR system with SPS assumption...