Energy Management in Heterogeneous Networks with Cell Activation, User Association and Interference Coordination

TL;DR

This paper proposes a novel energy-efficient resource management framework for heterogeneous wireless networks that jointly optimizes cell activation, user association, and interference coordination based on interference patterns and long-term traffic conditions.

Contribution

It introduces a new interference pattern-based resource allocation method and a tailored algorithm that significantly reduces complexity while improving energy savings.

Findings

Significant energy savings demonstrated in simulations.

Interference-aware user association improves network efficiency.

Cell-specific biasing differs from traditional load balancing strategies.

Abstract

The densification and expansion of wireless network pose new challenges on interference management and reducing energy consumption. This paper studies energy-efficient resource management in heterogeneous networks by jointly optimizing cell activation, user association and multicell multiuser channel assignment, according to the long-term average traffic and channel conditions. The proposed framework is built on characterizing the interference coupling by pre-defined interference patterns, and performing resource allocation among these patterns. In this way, the interference fluctuation caused by (de)activating cells is explicitly taken into account when calculating the user achievable rates. A tailored algorithm is developed to solve the formulated problem in the dual domain by exploiting the problem structure, which gives a significant complexity saving. Numerical results show a huge improvement in energy saving achieved by the proposed scheme. The user association derived from the proposed joint resource optimization is mapped to standard-compliant cell selection biasing. This mapping reveals that the cell-specific biasing for energy saving is quite different from that for load balancing investigated in the literature.