Limited Feedback Approaches based on Clustering in MIMO-OFDM Systems

This paper investigates some limited feedback approaches based on clustering in MIMO-OFDM beamforming systems with limited feedback. Exploiting the channel frequency correlation across adjacent subcarriers within a cluster, a low complexity channel mean clustering is proposed. In the approach, the optimal cluster beamforming vector is selected in a pre-designed codebook with mean channel response. Additionally, exploiting the residual frequency correlation between the cluster beamforming vectors, both recursive feedback and trellis-based feedback are proposed to reduce feedback rate. In the proposed approaches, the new codebook of current cluster consists of the codewords within in the neighborhood of previous cluster codeword, hence reducing the number of feedback bits remarkably. The simulation results show that, the channel mean clustering can obtain good BER performance with low computational complexity, and the feedback reduction approaches can further reduce feedback rate compared to traditional clustering methods. The recursive feedback approach has a little performance loss while the performance loss of the trellis-based feedback approach can be ignored.