Aggregated interference modeling based on WRAN

This article focuses on the modeling of aggregated interference in cognitive radio-based Wireless Regional Area Network (WRAN). We develop two distribution models to represent the spatial distribution of primary and secondary users, examining various factors that influence overall interference levels. The first model describes the aggregated interference experienced by primary user receivers due to secondary users within the network, assuming that the primary user's location is independent of the secondary user network and their receiver information is known. The second model considers the interference generated by secondary users within the network on primary user receivers, with both the primary user's location and receiver information being unknown. We derive the cumulative distribution function (CDF) for both models, employing a logarithmic normal distribution approximation to reduce computational complexity. Experimental results confirm the consistency between our analytical model and Monte Carlo simulations, validating the accuracy of our approach. Finally, we analyze the impact of key parameters such as secondary user density, transmitter power, and distance from primary to secondary users on cognitive network interference. These findings offer valuable insights for practical deployment of cognitive networks in real-world scenarios.