Power-shortage model with energy trading in green cloud RANs

In recent years, with the rapid development of mobile data at higher data rates, the overall power needs of receiving terminals may have exceeded the power budget of remote radio heads (RRHs). As a result, the network operator must get lots of energy from the real-time market again, especially the grid, or make less profit. This paper proposes two models to study energy management in real-time based on specific renewable energy at RRHs to address the following issue for green cloud radio access networks (Cloud-RANs). This paper proposed two models which formulate partial cooperation optimization problems in model 1 using a reweighted ℓl-norm approximation for ℓO-norm while model 2 proposed full cooperation optimization formulation. Then, both proposed models are applied semidefinite relaxation (SDR) techniques. According to the simulation results, the proposed model 2 efficiently minimizes energy costs to achieve better SINR targets and real-time energy trading while managing supply and demand power at RRHs and satisfying QoS at user terminals. The proposed model 2 with power-shortage management outperforms the other model regarding enabling energy efficiency and lowering total network energy costs.