Energy-Efficient and Load-Proportional eNodeB for 5G User-Centric Networks

Nowadays, dense network deployment is being considered as one of the effective strategies to meet capacity and connectivity demands of the fifth generation (5G) cellular system. Among several challenges, energy consumption will be a critical consideration in the 5G era. In this direction, base station on/off operation, i.e., sleep mode, is an effective technique to mitigate the excessive energy consumption in ultra-dense cellular networks. However, current implementation of this technique is unsuitable for dynamic networks with fluctuating traffic profiles due to coverage constraints, quality-of-service requirements and hardware switching latency. In this direction, we propose an energy/load proportional approach for 5G base stations with control/data plane separation. The proposed approach depends on a multi-step sleep mode profiling, and predicts the base station vacation time in advance. Such a prediction enables selecting the best sleep mode strategy whilst minimizing the effect of base station activation/reactivation latency, resulting in significant energy saving gains