With the emergence of 5G and future network generations aiming to accommodate a diverse range of use-case scenarios, the boundaries of traditional mobile systems are being pushed. This research delves into how well heterogeneous wireless networks perform when the signal experiences fading that follows the η-μ distribution model. It specifically focuses on the impact of user movement on network performance. By integrating the random waypoint (RWP) model with the η-μ distribution. We effectively model the dynamic behavior of non-homogeneous fading, also we express the probability density function (PDF) and cumulative distribution function (CDF) of received signal power in three-dimensional topologies. Additionally, we analyze the outage probability (OP) and average bit error rate (ABER) to assess mobile system performance, considering co-channel interference (CCI) effects from desired and interfering signals in mobile networks. The expression model characterizes mobile user performance, aiding in evaluating noise and interference impacts. We extend our analysis to various fading channels, including one-sided Gaussian, Nakagami-m, Rayleigh, and Nakagami-q (Hoyt) distributions. examining mobility's impact on these channels. Also examines the ergodic channel capacity (ECC) when users are moving according to a RWP mobility pattern. We express mathematical formulas to calculate this average capacity for various fading environment like η-μ, α-μ and α-η-μ fading channel. Montecarlo simulation validate the expression of η-μ fading model, providing insights into the effect of physical channel and mobility parameters. Lastly, we derive the Effective Energy Efficiency for the η-μ fading model, comparing static and mobile scenarios. This comprehensive analysis facilitates the design of robust 5G and beyond systems, ensuring better performance in diverse fading environments.
