Adaptive user association in HetNets with renewable energy powered base stations

Abstract

In this paper, we propose adaptive user association in the Heterogeneous Networks (HetNets) with renewable energy powered base stations (BSs), where all the BSs are assumed solely powered by the harvested energy from the renewable energy sources. BSs across tiers differ in terms of energy harvesting rate, maximum transmit power and deployment density. In conventional grid-powered HetNets, user association is determined based on the assumption that all the BSs can transmit with constant powers, whereas the transmit powers of BSs vary in the HetNets with renewable energy powered BSs. The adaptive user association is formulated as an optimization problem which aims to maximize the number of accepted user equipments (UEs) and minimize the radio resource consumption in the scenario where the available energy of BSs is dependent on the harvested energy in a certain period of time. We first propose an optimal offline algorithm, where the gradient descent method is used to achieve the pseudo-optimal user association solution. The performance of proposed gradient descent based user association algorithm is verified by simulation results. Considering practical implementation, we further propose a heuristic online user association algorithm which is capable of making timely user association decision for the incoming UEs based on remaining available network resources. Simulation result indicates the proposed online algorithm achieves good tradeoff between UEs acceptance ratio and association delay.