Joint User Association and User Scheduling for Load Balancing in Heterogeneous Networks - 2018


This Project 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 drawback. In order to efficiently solve the problem, we tend to first approximate the nonconvex throughput achieved with US to a concave perform, and demonstrate that the gap for such an approximation approaches zero when the number of users is sufficiently giant. Then, by exploiting a distributed convex optimization technique called alternating direction methodology of multipliers, a joint UA and US algorithm, that can be implemented on every user's side and base station (BS)'s side separately, is proposed to obtain the only-BS association and resource allocation solutions. A outstanding feature of the proposed algorithm is that aside from load balancing, multiuser diversity is exploited within the association method to more improve system performance. We have a tendency to also extend the algorithm style to multi-BS association, whereby a user is related to multiple BSs. The simulation results show the superior performance of the proposed algorithms and underscore the numerous edges of jointly exploiting multiuser diversity and load balancing.

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