Maximum power interference alignment scheme for less computational cost in MIMO interference channel

Maximum power interference alignment (IA) algorithm is typically used to find interference mitigation solution for MIMO interference channels (MIMO-IC). However, this iterative IA scheme brings tremendous computational cost. In this paper, we propose a new iterative IA algorithm that designed to finding the IA solution maximizes the power with less computational cost. The proposed algorithm combines the modified GramSchmidt sorted QR decomposition method and the steepest descent method on the Grassmann manifold to not only minimize the distances between the interference subspace and the subspace spanned by interference, but also further reduce the complexity of the whole system with each iteration. Simulation results show that it not only is the same basically in the system capacity, but also obviously decreases the system computational complexity.