Dynamically Energy-Efficient Resource Allocation in 5G CRAN Using Intelligence Algorithm

Abstract

5G network is the next generation for cellular networks to overcome the challenges and limitations of the 4G network. Cloud Radio Access Network(C-RAN) is providing solutions for cost-efficient and power-efficient solutions for the 5G network. The aim of this paper proposed an energy-efficient C-RAN to minimize the cost of the network by dynamically allocating BBU resources to RRHs as per facing traffic, and also minimize the energy consumption of centralized BBU resources that affect dynamically allocate of RRHs. Particle Swarm Optimization (PSO) algorithm is a Swarm Intelligence algorithm for optimization of mapping between BBU-RRH for resource allocation in C-RAN. The main objective of the paper is as per resource usage in C-RAN the BBU is put in the active or in-active mode to minimize energy consumption in C-RAN of 5G technology. As per our proposed C-RANapplication, the proposed PSO algorithm 90% minimizes energy consumption and maximizes energy efficiency compared with existing work.

Keywords

• 5G network
• C-RAN
• BBU
• RRH
• Front haul
• Swarm Intelligence algorithm