Parameter optimization using local search for CRE and eICIC in heterogeneous network

In heterogeneous network where picocells are overlaid onto macrocells, combined usage of cell range expansion (CRE) and enhanced inter-cell interference coordination (eICIC) is very effective in improving the system capacity. Two parameters of the CRE bias value and the ratio of ABS (almost blank subframe) affect each other. Thus, the comprehensive control of both parameters is very important to improve the system capacity and fairness among user equIPments (UEs). The conventional parameter optimization method, which uses the Nash bargaining solution, can keep fairness among UEs, while improving system throughput. However, a fixed pair of these parameters used in this method is not always appropriate due to varying distribution of UEs. In this paper, we focus on a convex characteristic of the cell-edge UE capacity for the ABS ratio and propose a parameter optimization using local search with small computational complexity. Simulation results show that parameter setting by the proposed scheme improves system capacity and cell-edge UE capacity, compared with the conventional approach.