  This paper studies the joint user association and resource allocation in
heterogeneous networks (HetNets) from a novel perspective, motivated by and
generalizing the idea of fractional frequency reuse. By treating the multi-cell
multi-user resource allocation as resource partitioning among multiple reuse
patterns, we propose a unified framework to analyze and compare a wide range of
user association and resource allocation strategies for HetNets, and provide an
optimal benchmark for network performance. The enabling mechanisms are a novel
formulation to consider all possible interference patterns or any pre-defined
subset of patterns, and efficient sparsity-pursuit algorithms to find the
solution. A notable feature of this formulation is that the patterns remain
fixed during the resource optimization process. This creates a favorable
opportunity for convex formulations while still considering interference
coupling. More importantly, in view of the fact that multi-cell resource
allocation is very computational demanding, our framework provides a systematic
way to trade off performance for the reduction of computational complexity by
restricting the candidate patterns to a small number of feature patterns.
Relying on the sparsity-pursuit capability of the proposed algorithms, we
develop a practical guideline to identify the feature patterns. Numerical
results show that the identified feature patterns can significantly improve the
existing strategies, and jointly optimizing the user association and resource
allocation indeed brings considerable gain.
