An Efficient Feedback Compression for Large-Scale MIMO Systems

Large-scale multiple-input multiple-output(MIMO) systems with a large number of antennas at the basestation have drawn considerable interest because of potential ability to achieve high spectral efficiencies. In order to achieve optimal performance of large-scale MIMO systems, the basestation needs to know channel state information (CSI) perfectly. In terms of CSI acquisition, the basestation estimates the downlink channel through channel reciprocity in time division duplexing (TDD) or requires CSI feedback through the uplink in frequency division duplexing (FDD). Due to the large number of transmit antennas at the basestation, uplink CSI feedback would be a major hurdle in developing FDD large-scale MIMO systems. In this paper, we propose an efficient feedback compression technique for FDD large-scale MIMO systems. The proposed method reduces a dimension of vector quantization by grouping high correlated antenna elements. In fact, the proposed method invests a small portion of feedback resources to generate a grouped channel vector and the rest to quantize the grouped channel vector. Simulation results demonstrate that the proposed method achieves significant feedback overhead reduction over conventional methods.