Energy Saving and Interference Coordination in HetNets Using Dynamic Programming and CEC

Abstract

Energy efficiency in cellular networks has gained great relevance due to the increasing power supply demands in new generation heterogeneous network (HetNet). On the other hand, interference coordination is a key aspect in HetNets resource management which directly affects the performance and energy consumption. Although these two aspect are intertwined, they have been studied separately so far. In this paper, we address the joint problem of energy saving and interference coordination in HetNets. We formulate the problem as a finite horizon Markov decision process (MDP) leveraging two facts: the user traffic demands usually follow periodic patterns, and the knowledge and prediction of network load is crucial in order to select efficient network configurations. Quality of Service (QoS) in the network is defined as the ratio of users meeting a requirement specified by the operator, and allows us to account for a minimum QoS requirement by including a constraint in the formulation of the MDP. To address this MDP, we propose an approximate dynamic programming (ADP) algorithm which selects energy efficient farsighted configurations with QoS guarantees achieving near optimal performance. This ADP algorithm is built upon: 1) the certainty equivalent control principle, which simplifies the complexity of the MDP, and 2) machine learning techniques: a neural network and a polynomial regressor which allow us to predict the QoS and the consumption of the network in advance. We evaluate our proposal in a LTE-A network simulator following the 3GPP guidelines, and the results obtained show that a joint control of the energy saving and interference coordination mechanisms results in a notably performance improvement compared to a disjoint control, in terms of both energy savings and QoS guarantees. Moreover, our proposal has the advantage of being adaptable to the operator QoS requirements.