The Research Of Load Balancing Based On Carrier Aggregation In Heterogeneous Network

Heterogeneous network has been considered as one of the key technologies for the next generation of mobile communication network. It provides flexible ways to improve spectral efficiency, balance the load of network and optimize cell-edge performance. At the same time, because of the new intermediate nodes and multi-layer network deployment, heterogeneous architecture brings challenges in terms of massive parameters setting. As one of the main functions in the self-organization network, load balancing could automatically adjust the distribution of network resource and enhance system performance. Therefore, it has drawn extensive attention. Load balancing in heterogeneous network is the research focus of this thesis.In this paper, we propose a novel two-step load balancing(LB) algorithm in self-organization network. The first step is modeling for LB optimization problem. Network flow based LB algorithm is applied in the first step to optimize the procedure of traffic transfer, this could balance the load status while minimize the burden on the system. Quick sort algorithm is utilized in the second step to select target handover users considering user capabilities. The second step could further reduce the number of inter-cell handover. The cell physical resource variety is also assumed in the presented algorithm to support the key feature in LTE-A system, 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 and the ratio of resource utilization in light-load cells are improved significantly. This paper further takes the energy saving(ES) issue into consideration with the LB algorithm and proposes the energy-efficient LB algorithm in heterogeneous network. The algorithm could be achieved via deploying the sleep-mode capable pico cells. The joint optimization of energy saving and LB could improve the energy efficiency while addressing the imbalanced load allocation caused by ES. In this paper, we introduce the strategy based on the prediction of load capability to select pico cells to enter sleep mode. Furthermore, network flow based LB is proposed to provide solution of redistribution caused by ES. System level simulations are conducted to exhibit the performance enhancement that the proposed algorithm can reduce energy consumption as well as improve the balanced degree of resource allocation significantly. Finally, further discussion about network energy efficiency is given. Through the utilization of stochastic geometry and nonlinear optimization theory, optimization analysis about the density of base station is proposed for the purpose of maximizing energy efficiency in the heterogeneous network.