One-sided Precoder Designs on Manifolds for Interference Alignment
  Interference alignment (IA) is a technique recently shown to achieve the maximum degrees of freedom (DoF) of $K$-user interference channel. In this paper, we focus on the precoder designs on manifolds for IA. By restricting the optimization only at the transmitters' side, it will alleviate the overhead induced by alternation between the forward and reverse links significantly. Firstly a classical steepest descent (SD) algorithm in multi-dimensional complex space is proposed to achieve feasible IA. Then we reform the optimization problem on Stiefel manifold, and propose a novel SD algorithm based on this manifold with lower dimensions. Moreover, aiming at further reducing the complexity, Grassmann manifold is introduced to derive corresponding algorithm for reaching the perfect IA. Numerical simulations show that the proposed algorithms on manifolds have better convergence performance and higher system capacity than previous methods, also achieve the maximum DoF. 
Chen Zhang, Huarui Yin and Guo Wei
cs.IT math.IT