Functional split in 5G cloud radio access network using particle swarm optimization

Abstract

The Cloud Radio Access Network (C-RAN) is an innovative approach that has the potential to significantly reduce the expenses of setting up and operating wireless networks. C-RAN's placement of RAN functions, which strives to reduce bandwidth utilization and computation costs, is a critical component. In this study, our main goal is to reduce the costs associated with functionally placing the RAN while accounting for the computational expense and the front-haul bandwidth usage among various users. To achieve this, we propose to apply Particle Swarm Optimization (PSO) to achieve effective allocation of computational resources and the front-haul bandwidth, ensuring an efficient and cost-effective C-RAN design. Experimental results on different traffic have shown that the proposed PSO can provide cost-effectiveness design of the C-RAN as compared to the optimal solution from the integer linear programing approach.