Multi-parameter Q-Learning for downlink Inter-Cell Interference Coordination in LTE SON

Inter-Cell Interference (ICI) is considered as the main reason for throughput degradation in cellular systems, especially for users at the cell edges. To mitigate ICI, ICI Coordination (ICIC) has been proposed in the context of Self Organization Networks (SON). In this paper, we present a Qlearning based ICIC algorithm, called Q-ICIC that learns for each cell the best configuration for two control parameters - the sub-band power factor and the edge-to-center boundary (ECB) so as to minimize ICI. We validate the algorithm with LTE system level simulations and show that Q-ICIC achieves considerable improvement in system performance in terms of Signal to Interference plus Noise Ratio (SINR), without compromising the coverage in the cells.