EE-eICIC: Energy-Efficient Optimization of Joint User Association and ABS for eICIC in Heterogeneous Cellular Networks

Abstract

The densification and expansion of heterogeneous cellular networks (HetNets) pose new challenges on interference management and reduction of energy consumption. The 3GPP has proposed enhanced intercell interference coordination (eICIC) by making a macrocell silent in almost blank subframes (ABSs) to mitigate interference for low power base stations (BSs) in HetNets. However, energy efficiency (EE) is very crucial for the deployment of a large number of low power nodes as they consume a lot of energy. In this work, we develop a novel EE-eICIC algorithm to determine the amount of ABSs and user equipment (UE) that should associate with picocells or macrocells from energy efficiency perspective. Due to the nonsmooth and mixed combinatorial features of this formulation, we focus on a suboptimal algorithm design. Using generalized fractional programming and the convex programming theory, we propose an iterative and relaxed-rounding algorithm to solve the problem. Numerical results illustrate that the proposed EE-eICIC algorithm achieves superior performance in comparison with state-of-the-art methods in terms of energy efficiency of both system and user.

Resource Allocation for Energy Efficiency and QoS Provisioning

“…With network planning and development, infrastructure changes are done to maximize the covered area per consumed energy instead of just maximizing the coverage. As an example, power consumption can be reduced through switch-on/switch-off algorithms, where during low traffic periods the system can turn off underutilized Base Stations (BSs) and transfer their loads to neighboring BSs [11]. With energy harvesting, transceivers collect (harvest) energy from the environment, including radio signals, wind and solar energy, and use it for information processing and transmission [7].…”