The study of load balancing based on the network flow theory in LTE-A systems

In order to reduce the necessary manual intervention in network operation, self-organization and self-optimization of wireless communication systems are introduced. Automatical load balancing (LB), which can decrease the evolved Node B (eNB) overloading and improve the network capacity, draws much attentions from both network operators and manufactures in recent years. In this paper, we propose a novel two-step network flow based mobility LB (NFT-MLB) algorithm in self-organizing network (SON). Network flow theory is applied in the first step to optimize the procedure of overload traffic transfer, and then the user equipment (UE) capabilities are considered to select the specific handover users. The cell physical resource variety is also assumed in the presented algorithm to support the key feature in long term evolution-advanced (LTE-A) systems, i.e., carrier aggregation. System level simulations are conducted to exhibit the performance improvement of the proposed LB algorithm. It is shown from the results that the load distribution index and average load ratio are improved significantly.