Dynamic and Energy-Efficient Resource Allocation using Bat Optimization in 5G Cloud Radio Access Networks
S. Padmakala, Mohammed Al‐Farouni, Deepak Dasaratha Rao, K. Saritha, R P Puneeth
Abstract
G networks represent the fifth iteration of cellular networks, thus aimed at resolving the challenges and constraints faced by the preceding 4G network. Cloud Radio Access Networks (CRAN) provides economical and EnergyEfficient (EE) solutions customized to the requirements of 5G networks. This research proposes an energy-efficient CRAN that automatically allocates Baseband Unit (BBU) resources to Remote Radio Unit (RRHs) based on traffic, increasing network throughput as well as reducing power usage. Bat Optimization Algorithm (BOA) is a Swarm Intelligence (SI) approach used to optimize Resource Allocation (RA) in CRAN by mapping BBURRHs. Through controlling the BBU’s mode based on resource utilization, this research minimizes the Power Consumption (PC) in 5G CRAN. Moreover, the findings revealed that the proposed BOA-CRAN reduced the power usage upto 95% when compared to existing methods such as 5G CRAN, Green-RAN while increasing BBU efficiency.