Interference Alignment with Single Feedback for Downlink Cellular Networks

Interference is one of the key performance metrics in the design of cellular networks; Interference Alignment (IA) can eliminate the impact of interference and improve the capacity performance of cellular networks. In classic IA algorithms for downlink cellular networks, users improve the performance from their own point of view, so limit the sum capacity of cells. A new IA technique for downlink cellular networks is proposed in view of improving the sum capacity performance of per cell. Downlink IA mathematics model for cellular networks is constructed, receive vector is chosen to maximize SINR at the receivers, and precoder matrix is created by gradient projection method to maximize the sum capacity of per cell at base-stations. Numerical results show that the new algorithm has better capacity performance than classic downlink IA algorithms for cellular networks.