Channel Allocation Optimization for Concurrent Communications in Fifth-Generation Networks Using the Hippopotamus Optimization Algorithm

Abstract Optimal channel allocation in fifth-generation (5G) cellular networks plays a vital role in ensuring quality of service and reducing call blocking rates. In this study, an innovative model based on the hippopotamus optimization algorithm (HOA) is proposed to enhance channel allocation efficiency. To evaluate performance, six simulation scenarios were designed under various conditions, ranging from heavy traffic to abundant resource availability. In these scenarios, the number of active users varied between 30,000 and 40,000, the available channels ranged from 3,000 to 5,000, the call arrival rate spanned 0.7 to 0.99 calls per hour, and the average call duration ranged from 3.6 to 28.5 minutes. Compared with three well-established methods—genetic algorithm, Ant colony optimization, and particle swarm optimization —the proposed HOA demonstrated, on average, a 19% reduction in call blocking rates and achieved faster convergence speed. Despite these advantages, limitations such as increased computational complexity in very large-scale scenarios remain, which may define directions for future research. The results highlight the significant potential of HOA in improving spectrum efficiency, enhancing network capacity, and elevating user experience in 5G cellular networks.