The correlation of interference has been well quantified in Poisson networks where the interferers are independent of each other. However, there exists dependence among the base stations (BSs) in wireless networks. In view of this, we study the interference correlation in non-Poisson networks where the interferers are distributed as a Matern cluster process (MCP) and a second-order cluster process (SOCP). We obtain the explicit expressions for the interference correlation coefficients under these two cases and find that they are the same if these two cluster processes have the identical cluster radius and average number of each cluster. We also prove that they are greater than their counterpart for the Poisson networks, which indicates the clustering in interferers increases the interference correlation. It is also shown that the value of the correlation coefficient goes up as the the attraction between the interferers increases. Finally, the numerical results show the relation between the correlation coefficients and system parameters.
Capturing the correlation in user locations in wireless networks, REF studied interference correlation in clustered networks (modeled as Matern or Thomas cluster process) and showed that clustering of interferer locations enhances interference correlation.
Analysis of Interference Correlation in Non-Poisson Networks
2016 IEEE Global Communications Conference (GLOBECOM)
2016 IEEE Global Communications Conference (GLOBECOM)
Computer Science Mathematics