ABSTRACT The next‐generation wireless technology modernizes the telecommunication infrastructure by incorporating cloud‐based services into its existing framework. Cloud radio access network (C‐RAN) was introduced in the 4G era and became popular in recent trends due to the flexibility of sharing resources and decoupling of the data plane and control plane. While this decoupling improves radio resource allocation and processing efficiency, it also introduces challenges in optimizing routes between user equipment (UE), remote radio heads (RRHs), and baseband units (BBUs) under diverse QoS requirements. In this work, the route optimization problem for 5G C‐RAN architecture is formulated by developing an optimization function for a dense urban network that consists of 500 UEs connected to 100 RRHs and further linked to 20 BBUs via fronthaul connections. To enhance path selection and routing optimization, several nature‐inspired algorithms, that is, ACO, WOA, PSO, GWO, CSO, BOA, and SMO are applied, as these methods are effective for solving complex optimization problems. The performance of these algorithms is analyzed in terms of best fitness value, network efficiency, number of satisfied users, number of blocked users, and number of dropped users under high traffic density. To reduce the impact of randomness in the search process, the experimental results are statistically validated using ANOVA and Tukey's post hoc tests. A detailed comparison of nature‐inspired algorithms utilized in this work has been carried out to evaluate their performance, which further confirms the practical suitability and advantages of ACO in 5G C‐RAN systems.
Kumar et al. (Tue,) studied this question.