Experimental Verification on the Prediction of the Trend in Radio Resource Availability in Cognitive Radio

Abstract

This paper presents a prediction of the trend in radio resource availability in cognitive radio. In this paper, cognitive radio is defined as the wireless communication technology in which each node communicates via an optimal wireless system based on recognition of the radio resource availability in heterogeneous wireless communication systems. We focused on the prediction of the network allocation vector (NAV) value for radio resource availability in IEEE 802.11, which is one of the candidates for installation in a cognitive radio [1]. We verified the prediction of the future value of the trend in the NAV time series; based on an auto-regressive model (AR model) and using captured data within a real environment. Based on the results of the verification, we show that prediction based on the AR model with suitable parameters is applicable in comparison when the average of the last 10 samples is used as a predicted value and the case where prediction is not applied. Furthermore, it is possible to set up a long update interval for the regression coefficients.