A Novel Bio-Inspired Energy Optimization for Two-Tier Wireless Communication Networks: A Grasshopper Optimization Algorithm (GOA)-Based Approach

Energy consumption has become one of the most challenging problems in future wireless communication networks. One promising methods fifth generation (5G) cellular networks to meet ever-increasing demand for high data traffic is heterogeneous (HetNets). Adding more base stations may improve network coverage, but leads a significant amount power. The scheme two-tier contains small cell (SCBs) that cooperate with macro (MCBs) provide wider coverage. Some station SCBs are experiencing light loads due movement user equipment (UEs), these still consume considerable energy. Therefore, reduce SCBs’ power and maximize overall energy efficiency (EE) network, some need be switched off. In this paper, we extend operation modes BSs present novel mechanism select an appropriate mode each SCB based on bio-inspired behavior. We employ bias function manage mode. Each four selections: On, Standby, Sleep, Off. formulate EE maximization problem under set constraints Grasshopper Optimization Algorithm-based Variant Power Mode Selection (GOA-VPMS) solve it. proposed algorithm outperforms previous work provides higher EE, according simulation results.