QoS-Aware Load Balancing in Dense Cellular Networks with Dynamic User Traffic

Due to the dense deployment of small cells, the number of mobile users served by each access point is decreasing dramatically, which leads to an increasingly dynamic cell load distribution over time and space. In order to match dynamic traffic load with static infrastructure capacity, a variety of load balancing methods have been proposed. However, the existing load balancing approaches either run self-tuning algorithms to optimize local handover parameters, which may not be optimal for the network-wide performance, or formulate a static optimization problem for a "snapshot" network, which may require a huge amount of handover signaling in dynamic situations. In this paper, we consider the load balancing problem with dynamic traffic models, in which the average throughput over a certain time period is maximized, while the average packet delay is guaranteed to be below a certain threshold. Simulation results show that our proposed user association and resource allocation algorithm can highly increase the average throughput, compared with the baseline algorithm using the maximum SINR association and equal resource allocation.