Joint User Association and User Scheduling for Load Balancing in Heterogeneous Networks

This paper investigates joint user association (UA) and user scheduling (US) for load balancing over the downlink of a wireless heterogeneous network by formulating a network-wide utility maximization problem. In order to efficiently solve the problem, we first approximate the nonconvex throughput achieved with US to a concave function, and demonstrate that the gap for such an approximation approaches zero when the number of users is sufficiently large. Then, by exploiting a distributed convex optimization technique known as alternating direction method of multipliers, a joint UA and US algorithm, which can be implemented on each user's side and base station (BS)'s side separately, is proposed to obtain the single-BS association and resource allocation solutions. A remarkable feature of the proposed algorithm is that apart from load balancing, multiuser diversity is exploited in the association process to further improve system performance. We also extend the algorithm design to multi-BS association, whereby a user is associated with multiple BSs. The simulation results show the superior performance of the proposed algorithms and underscore the significant benefits of jointly exploiting multiuser diversity and load balancing.