A Stochastic Geometry Approach to Performance Modeling of SWIPT Vehicular Networks

With the increasing number of devices and the advent of 5G and 6G networks, ensuring reliable power and data connectivity remains a significant challenge, particularly in rural or remote areas. Simultaneous Wireless Information and Power Transfer (SWIPT) networks have emerged as a promising solution to power devices without batteries. However, their deployment in real-world scenarios is hindered by complex channel conditions and spatial dynamics. This research introduces a two-tier analytical model grounded in stochastic geometry, where base stations (BSs) are arranged along roads following a Poisson Line Cox Process (PLCP), while user equipment (UEs) is distributed using a Poisson Point Process (PPP). A comparative evaluation against planar PPP-based models demonstrates the performance advantages of this novel approach. Additionally, a Genetic Algorithm (GA) is applied to explore real-world scenario parameters, enhancing the model's adaptability and performance in practical applications.