Subchannel Allocation Scheme for Two-tire Femtocell Networks Based on Q-learning

In order to improve the spectrum efficiency in the Femtocell home Base Station (FBS) heterogeneous network, FBS and Macrocell Base Station (MBS) are usually deployed with the same frequency. However, the same frequency deployment will inevitably lead to larger co-channel interference. In order to achieve the large-scale deployment of FBS, reducing the interference of the network with the channel is particularly important. In this paper, a sub channel allocation scheme is propsed based on Q-learning. It can ensure that FBS will not bring high cross-layer interference of MBS, while it reduces the same layer interference between two FBS. The simulation of the algorithm of FBS sparse deployment and dense deployment situation are performed, respectively. Simulation results show that this algorithm reduces the same layer interference and verifies the correctness of the theory.