Machine Learning-User Association Approach for Energy-Efficient and Mitigation Interference in HetNets
Samira Achki, Layla Aziz, Sanaa Kabil, Abdelali El Gorari, Ait Lahcen Yassine · 2025
The requirement for the use of equipment mobile services increases every day. This requires the consumption of energy rates and increases the interference between equipment. Hence, minimizing the energy and mitigating the interferences of mobile users are the major key concerns of Heterogeneous Networks (HetNet). The objective of this chapter is to enhance the energy of mobile users and minimize interference, using the machine learning method to associate the users toward the optimal base station (BS). We considered the important criteria influencing energy consumption and interference. Moreover, we introduce an optimal user association for BS. Simulation results show that the optimal method has saved more energy and reduced network interferences.