Throughput and load balancing optimization in heterogeneous networks using Red-Tailed Hawk Algorithm

In wireless communication networks, the growing need for data has presented significant issues in the last years. This will continue, with mobile consumers' needs for Quality of Service (QoS) changing and their data use skyrocketing. The complexity of Heterogeneous Network (HetNet) situations and the sharp rise in traffic demand have significantly increased the issues. It is challenging to accommodate the various traffic needs of mobile users with traditional methods as they maintain network imbalances inside the HetNets by giving priority to maximum received power in the cell association process. In this work, a Red-Tailed Hawk (RTH) algorithm with a Cell Range Extension (CRE) approach is integrated to maximize the number of users whose downlink demands are fulfilled, rather than just focusing on improving downlink rates for individual users. The suggested approach formulates a fitness function with the goal of determining appropriate CRE bias values for individual Small Base Stations (SBSs) while taking into account the workload of BS as well as the Signal to Interference-plus-Noise Ratio (SINR) of user devices. The efficiency related to the suggested strategy is demonstrated by a comparison with conventional methods. The proposed methodology meets user throughput requirements while lowering network imbalances and call drop rates. Experimental findings demonstrate the betterment of the proposed model by 56.67% load balancing, 49.23% throughput, 91.49% call drop rate, 77.55% execution time, 92.68% delay, and 20.11% convergence than the existing methods.