An effective model for network selection and resource allocation in 5G heterogeneous network using hybrid heuristic-assisted multi-objective function

Abstract

Multiple service requirements in various communication environments are fulfilled by the fifth-generation (5G) mobile communication network. Heterogeneous Networks (HetNet) have been introduced as a newly developed network structure. Conventional cellular networks have prominent limitations in terms of frequency utilization, coverage, proliferation of transmission services, and power consumption. The previously used approaches provide precise results but are time-consuming, making them tricky to apply for huge networks, and makes them complicated to solve multifaceted problems. In order to decrease complementary interference and accomplish spectrum sharing, an effective resource allocation technique is necessary. Likewise, interference produced by the potential Secondary Users (SUs) must be kept at a minimum value within the authorized network. Considering the perspective of the supplementary networks, it is vital to delegate networks to SUs in order to lower the gross contamination and manage the overall network’s quantity. An efficient method is developed on a heuristic basis in order to solve the issues regarding resource allocation in 5G networks. With the aid of every user device’s network properties, network selection, and resource allocation are considered the two major concerns that need to be attained in 5G heterogeneous network systems. To meet this requirement, the multi-objective constraints are considered with the help of the Integrated African Vultures with Grasshopper Optimization Algorithm (IAVGOA). The constraints that are taken into consideration are communication cost, interference between all the SU to the primary user, Quality of Service (QoS), and congestion control. The performance of the executed model is examined using various metrics. When compared with the existing models, the proposed method achieves impressive results in appropriately selecting the network and allocating the resources over 5G networks.