Performance analysis in cognitive radio system under perfect spectrum sensing

Abstract

Sensing period and optimization of user access in cognitive radio system are analyzed. By introducing birth and death process into cognitive radio system, a model of the queuing of primary users is built, based on which the probability of spectrum sensing and how the re-enter of the primary users effect on the spectrum usage of cognitive radio users are studied theoretically. Simulation results have justified the fitness of the model of joint analysis in the practical environment. Therefore we may conclude that it will achieve the highest overall spectrum efficiency by setting up configurations in a cognitive system according to the theory above. cognitive radio technology resources, according to the business needs, user access characteristics, spectrum sensing methods and some other characteristics of the cognitive system , system modeling, parameter optimization, performance analysis and some other researches were made in the existing literatures. In (3), the appearing characteristic of PU was described by Continuous-Time Markov Chain (CTMC). Cumulative time and distribution probability of PU's occupying channel were met by analyzing. In (4) and (5), cognitive radio system was system modeled by state5's and state8's CTMC. Then, Secondary User (SU) access optimization algorithm was put forward and the spectrum utilization efficiency and user fairness were in good compromise. In (6), according to the SU's coexistence of different types, the system was modeled by Markov model stack. Markov chains of different states were established and were connected by few core states. The method simplified the modeling and analysis of SU of multiple types' cognitive radio systems. In (7), cognitive radio system model was established based on restaurant game theory and Semi-Markov process. The analysis complexity of cognitive radio system was reduced effectively under the subjective effect and system analysis frame was constructed based on social dynamic influence. In (8), for VolP business, general Markov chain model was established and adjacent transition relations of states are solved. User connection properties and data packet loss performance were analyzed. The simulation shows the system model was effective. Markov chain was introduced to model for the cognitive radio system in the literals above. System performance has been analyzed and optimized for parameters and conditions of different systems. It can be seen that the continuous-time Markov chain can describe the cognitive radio system very well. Based on this characteristic, under ideal testing conditions, this paper has conducted the system model with CTMC-N. System general equation is established and the system of equations of general solution is given based on flow equilibrium theory. Finally, relations between collision probability, channel utilization, SU arrival identity the number of channels and the false detection probability are analyzed and described through the numerical simulation of the system.