  Codebook design is one of the core technologies in limited feedback
multi-input multi-output (MIMO) communication systems. However, the
conventional codebook designs usually assume MIMO vectors are uniformly
distributed or isotropic. Motivated by the excellent classfication and analysis
ability of clustering algorithms, we propose a K-means clustering based
codebook design. First, large amounts of channel state information (CSI) is
stored as the input data of the clustering, and finally divided into N clusters
according to the minimal distance. The clustering centroids are used as the
statistic channel information of the codebook construction which the sum
distance is minimal to the real channel information. Simulation results consist
with theoretical analysis in terms of the achievable rate, and demonstrate that
the proposed codebook design outperforms conventional schemes, especially in
the non-uniform distribution of channel scenarios.
