Joint Resource Allocation and User Association in Multi-Antenna Heterogeneous Networks

Abstract

We study the joint optimization of resource allocation and user association in downlink multi-antenna heterogeneous networks. The resource allocation is done orthogonally in the spectrum while the user association is implemented using cell range extension. The objective is to maximize a user utility function that depends on the rate of the typical user. We resort to the Gil-Pelaez Inversion Theorem to approximate the coverage probability and present a concave formulation of the joint optimization problem. By interpreting the problem as a multi-criterion one, we propose a suboptimal user association policy. We show that the optimal resource allocation factor of each tier is equal to the optimal association probability, which can be efficiently computed using a standard convex optimization solver. Simulation results show significant (up to three times) rate gains when resource allocation is jointly optimized with user association in comparison with merely optimizing resource allocation with max-power user association.