Context-Aware User Association for Energy Cost Saving in a Green Heterogeneous Network with Hybrid Energy Supplies

In this paper, we study the user association problem to minimize the total energy cost for a green heterogeneous network with hybrid energy supplies. The power consumption of a BS in both the access network and the backhaul links are modeled. We formulate a constrained total energy cost minimization problem, which is generally hard to tackle. We propose a centralized algorithm that exploits the available context-aware information of the network, including the network architecture knowledge, users' data requirements, and available green energy, to find a feasible and near-optimal solution. Since it is difficult to collect all information in a heterogeneous network, we also propose a distributed algorithm based on the available context-aware information of each BS's own. Simulations are used to compare our algorithms with the maximum channel gain (MCG) algorithm and the max-RSRP algorithm. Results demonstrate that the proposed context-aware user association algorithms can significantly reduce the total energy cost.