Interference mitigation and capacity optimization in cooperative public femtocell networks with cognitive enabled multi-element antennas

To successfully deploy multi femtocells in public places, the interference between femtocells must be mitigated. However, some unique features of femtocells present a challenge in interference mitigation, such as complex indoor wireless environment and short distance between femtocells. In this paper, a novel low cost cognitive enabled multi-element antenna solution is proposed to reduce the intra-tier interference and optimize the network capacity. With low side-lobe, multi-element antennas can significantly reduce the interference to adjacent femtocells. Meanwhile, by applying cognitive capability, femtocells can sense the network environment and work in a Coordinated Multipoint Transmission (CoMP) way to jointly select antenna patterns. To achieve the optimum antenna patterns among multiple cooperative femtocells, a novel Graph Theory Based Coordinated Scheme (GTBCS) algorithm is applied to solve the optimization problem with an optimal weighted matching. Numerical results show that by combining the advanced technologies with the novel algorithm, especially applying graphical theory in antenna pattern selection, considerable capacity improvement and significant complexity reduction has been achieved.