Energy Efficient Resource Allocation in Heterogeneous Cloud Radio Access Networks

Energy harvesting is becoming an attractive option of energy supply for wireless networks as it can effectively reduce capital expenditure (CAPEX) and operational expenditure (OPEX). In this paper, an energy efficient radio resource optimization algorithm is proposed for a two-tier heterogeneous cloud radio access network (H-CRAN) where macro cells are empowered by conventional grid power and remote radio heads (RRH) are empowered by renewable energy sources. The resource allocation optimization is firstly formulated as a mixed integer programming problem, which is NP-hard. Therefore, an equivalent green power utilization maximization problem is formulated, and solved by Lagrange dual decomposition method. Numerical results show that the proposed algorithm can increase the utilization of the green power harvested from the renewable energy sources. This, in turn, leads to reduced grid power consumption compared to the baseline algorithms.