Energy efficient dynamic resource allocation in C-RAN using tunicate swarm and whale optimization algorithm

In Cloud radio access network (C-RAN) architecture, the signals are processed through cloud-computing method where the baseband units (BBUs) of all base stations are accumulated into a centralized BBU pool, while radio frequency (RF) functions are carried out easily at low-cost remote radio heads (RRHs). However, the BBUs are responsible for more complex network computational tasks that consume more energy. Thus, to reduce the energy consumption rate and to provide allocation of resources with the fulfillment of Quality of Service (QoS) in C-RANs, we have proposed a dynamic resource allocation method based on tunicate swarm whale optimization (TS-WO) algorithm. The TS-WO not only reduces the energy consumption problem of BBU but also reduces the energy consumed by RRHs with the optimal deployment of both BBU and RRHs. By this way, the number of RRH and BBU are reduced, and only the required sets of RRH and BBU are deployed guaranteeing less operator cost. After deployment, further a utility based active/sleep mode selection of both RRH and BBU is made to again reduce the energy, since the unused active nodes always consumes some energy.