Statistical interference modelling and deployment issues for cognitive radio systems in shadow fading environments

The authors deal with the issues of statistical modelling of the aggregate interference because of cognitive radios (CRs) at primary users and the deployment of CR systems in real world environments. The authors explore the possibilities of modelling the interference by two- and three-parameter log-normal distributions. The authors find that the traditional approach of using a two-parameter log normal is not a suitable option on account of the massive skewness difference between the actual interference and the log-normal variable used for fitting purposes. Similarly, the authors observe that the recently proposed three-parameter log-normal approximation works only under specific scenarios. While probing these issues, the authors also arrive at a considerably simpler way of deriving the cumulants of the total interference. Owing to analytical difficulties, the authors resort to simulations to assess different CR deployment schemes. Based on CRs equipped with a priori knowledge of the radio environment map (REM), the authors compare various CR system design parameters achieved by the proposed techniques. Furthermore, the authors describe the effect of imperfections in the REM information on the performance of CR systems. Via analysis and simulations the authors explore the relationship between the required precision of the REM and various system properties.