Generation of Optimal Almost Blank Frames using Genetic Algorithm

Abstract

The interference suffered by users at the CRE area of pico cells is one of the main factors that affects performance of a HetNet. In order to assist pico downlink transmissions, the Macro-eNB can mute all downlink transmissions to its users in certain subframes termed ABS. In this paper, we propose a genetic algorithm to find optimal ABS pattern that maximizes the network capacity and provides better fairness in resource allocation between all users. Results indicate that the ABS pattern provided by GA achieve a Fainess Jain Index 59,63% better compared with use of random pattern.