Interference alignment: Precoding subspaces design

Recently, the capacity region of the Single Input Single Output (SISO) fading interference channel has been characterized. Its degree of freedom is upper bounded by K/2. This upperbound can be asymptotically achieved using the Interference Alignment approach (IA), proposed by Cadambe et al. Our work aims to maximize the network sum rate of the IA scheme through the precoding subspaces design. We propose two designs. One is obtained as a closed-form solution of a constrained optimization problem when a Zero-Forcing decoding scheme is employed. The other is a generalized version of the optimized 3-user beamforming vectors design proposed by Kim et al., where a Minimum Mean Square Error receiver is utilized. This design presents a high computational complexity compared to the analytical solution obtained when assuming a ZF receiver. Simulation results illustrate the data rate performance and highlight the comparison between the different designs.