An Iterative Algorithm with Adjustable Weight for Inference Channel

In multiple-input multiple-output interference channels, Interference alignment suffers from performance loss at low Signal-to-Noise Ratio (SNR) due to it neglecting the desired signal power. An algorithm is proposed that iteratively minimizes weighted sum of leakages caused by both interference and desired signal out of their corresponding subspace. The weighted factors are allowed to be adjusted according to SNR. Simulation result shows that the proposed algorithm can improve sum rate effectively at low SNR.