QoS-Aware Load Balancing in 3GPP Long Term Evolution Multi-Cell Networks

In this paper, we investigate load balancing problem in 3GPP Long Term Evolution (LTE) networks and propose our solution which considers users with different Quality-of-Service (QoS) requirements. Load unbalance among neighboring cells often yields negative impacts on user experience and network performance, and it has mainly been considered for only data services without QoS guarantee. However, 3GPP LTE network aims to support multi-class services with different QoS requirements, on which the influence of load unbalance is quite different. For those with minimum rate requirements, it may result in high block probability, while for others without rate requirements, the throughput of boundary users may be degraded. In this paper, we incorporate all the differences into a network utility maximization framework and formulate it as a multi-objective optimization problem. The objectives in the problem are load balancing index of services with QoS requirements and the total utility of other services, and the constraints are physical resource limits and QoS demands. Then we analyze the complexity of the problem, and propose our solution, which includes a QoS guaranteed hybrid scheduling scheme, handover of users with and without QoS requirements, and a call admission control algorithm. Extensive simulation is conducted and the results show that the proposed framework leads to significantly better load balancing, and thus the decrease in call block probability of users with QoS requirements, and the increase in throughput of boundary best effort users.