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Mathematical Problems in Engineering
Volume 2016, Article ID 4567625, 11 pages
Research Article

A Submodular Optimization Framework for Outage-Aware Cell Association in Heterogeneous Cellular Networks

1School of Communication and Information Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
2Shenzhen Key Laboratory of Advanced Communications and Information Processing, Shenzhen University, Shenzhen 518060, China

Received 3 November 2015; Revised 3 February 2016; Accepted 11 February 2016

Academic Editor: Luciano Mescia

Copyright © 2016 Gongchao Su et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


In cellular heterogeneous networks (HetNets), offloading users to small cell base stations (SBSs) leads to a degradation in signal to interference plus noise ratio (SINR) and results in high outage probabilities for offloaded users. In this paper, we propose a novel framework to solve the cell association problem with the intention of improving user outage performance while achieving load balancing across different tiers of BSs. We formulate a combinatorial utility maximization problem with weighted BS loads that achieves proportional fairness among users and also takes into account user outage performance. A formulation of the weighting parameters is proposed to discourage assigning users to BSs with high outage probabilities. In addition, we show that the combinatorial optimization problem can be reformulated as a monotone submodular maximization problem and it can be readily solved via a greedy algorithm with lazy evaluations. The obtained solution offers a constant performance guarantee to the cell association problem. Simulation results show that our proposed approach leads to over 30% reduction in outage probabilities for offloaded users and achieves load balancing across macrocell and small cell BSs.