QoS_aware user association for load balancing in heterogeneous cellular network with dual connectivity

A novel QoS_aware user association algorithm for load balancing in heterogeneous cellular network with dual connectivity is proposed, where the best combination of macro cell and small cell for each user to associate is determined and the optimal traffic split between the macro cell and small cell is selected. Considering both guaranteed bit rate (GBR) users and Best Effort (BE) users, user association problem is formulated as a multi-objective optimization model. Furthermore, the objective function for GBR users is a joint optimization of the load balancing index and average load of the network, and the objective function for BE users is to maximize the utility function of the throughput of BE users. Firstly, a decomposition method is presented to analyze the original model in consideration of the computational complexity and quality of service (QoS) priorities of different users. Secondly, we adopt the greedy algorithm to solve this problem. Simulation results demonstrate that the proposed algorithm can decrease call blocking probability and improve throughput of boundary BE users, while achieving better load balancing.