Abstract:

Limited feedback interference alignment quantizes channel state information to reduce the amount of information of feedback. But classic limited feedback interference alignment algorithms only quantize the channel state information, and limited to theoretical analysis. Considering that the precoding matrix has much greater feedback data than channel state information. A new distributed interference alignment algorithm based on grassmannian codebook is proposed in view of reducing the impact of precoding matrix on feedback channel in distributed interference alignment, precoding matrices and decoding matrices are quantized based on grassmannian codebook, and are optimized for minimizing the interference leakage. The simulation results show that compared with the perfect feedback, when the signal noise rate of transmitters is less than or equal to 15 dB and the numbers of iteration are less than or equal to 10, the algorithm presented in the paper can effectively decrease the feedback data while the capacity close to the system with perfect channel state information.

Key words: multiple input multiple output, interference alignment, limited feedback, Grassmannian codebook, chord distance