Inter-cell downlink co-channel interference management through cognitive sensing in heterogeneous network for LTE-A

Heterogeneous network for long term evolution advanced (LTE-A) creates severe interference. It is an urgent task to overcome the interference in macro cellular with low-power base stations (BSs), such as relay, pico, and femto called subnet nodes. In this paper, the cognitive interference model in interference zone (IZ) of the practical heterogeneous scenario is proposed. Based on investigation of interaction between the macro BS and subnet nodes in this model, the strategy framework of the cognitive critical ratio and power reward factor is set up for interference management aiming to get the maximum net saving power. The study of interference management is transformed into a multiple objective non-linear programming (MONLP) of the maximum saving power for the macro BS and subnet nodes. To facilitate the best compromise solution for both, the MONLP is changed into single objective programming and genetic algorithm (GA) is employed to obtain the global optimum solution. In addition, the practical implementation using the proposed algorithm in heterogeneous network for LTE-A is designed. Finally, numerical evaluation is used to test the applicability of the proposed algorithm, and system level simulation results demonstrate the effectiveness of the proposed interference management scheme.