Traffic Pattern Prediction and Performance Investigation for Cognitive Radio Systems

Abstract

In this paper, we propose a technique for predicting the traffic pattern of primary users in cognitive radio systems. Cognitive radios enable sharing the frequency bands that are licensed to primary users. By forecasting the traffic pattern of primary users, secondary users can estimate the utilization of frequency bands and select one for radio transmission to reduce the frequency hopping rate (the rate of switching from one frequency band to another) and the interference effects, while maintaining a reasonable blocking rate. In this work, we propose an algorithm for the prediction of call arrival rate which exploits the periodicity of the traffic process. In addition, we present an approach for call holding time estimation. The results are incorporated to evaluate the probability of the availability of a frequency band within a time period. Setting a threshold on this probability maintains a tradeoff between the blocking rate of secondary users, interference effects on primary users and spectrum efficiency. Simulations are conducted to investigate the performance of cognitive radio systems with and without traffic prediction.