Energy efficiency optimization of resource allocation in hierarchical HetNetsDOBRUNA, JETA (Avtor) Volk, Mojca (Mentor) HetNetsuser associationresource allocationpower managementinterference coordinationenergy efficiency (EE)scalabilityquality of service (QoS)heuristic approachswitch ON/OFF techniqueWith the rapid advancement of technology, access to wireless services has become a daily necessity. In response to this need, network densification techniques are being deployed in which low-power Base Stations (BS), also called small BSs, are introduced in the same coverage and frequency range as the macro BSs, thus introducing the concept of a heterogeneous network (HetNet). HetNets are considered the principal architectural concept in future communication networks, especially in the Fifth Generation (5G) and the Sixth Generation (6G) networks. The ultra-dense deployment of small cells in HetNets has raised serious concerns regarding interference and energy consumption. Resource allocation and user association are the main approaches used to address these challenges. Today, numerous different strategies exist, depending on the chosen approach and the optimization targets pursued. Two important interrelated targets are interference coordination and energy efficiency (EE) optimization; improved EE can significantly reduce the operator’s operational costs, and better interference coordination leads to more efficient energy consumption. However, the complexity of finding an optimal solution increases when an ultra-dense HetNet scenario is considered. The main objective of this thesis is to develop a user association and power management algorithm that follows a heuristic approach and aims to maximize energy efficiency (EE). The proposed algorithm follows a heuristic approach for associating users with the BSs and exhibits low complexity. The switch ON/OFF technique is applied to manage power consumption. By implementing this technique, the proposed algorithm turns off the BSs that do not serve any users, as well as the macro BSs that have the largest impact on the network aggregated EE. The performance of the proposed algorithm is evaluated in a reference two-tier HetNet, considering all types of interferences. To validate the performance, we compared the proposed solution with two selected benchmarking solutions based on the eICIC technique and Lagrangian dual decomposition, respectively. The simulation results show that by minimizing energy consumption, the proposed solution outperforms the two benchmarking solutions in terms of EE and average user rate.20252025-02-20 11:10:01Doktorsko delo/naloga167408sl