LFC: Adaptive location-based CSI feedback compression for MU-MIMO networks

MU-MIMO proposed in 802.11ac is to achieve higher data rate, with transmitting to multiple users concurrently. However, the overhead cost by collecting channel state information (CSI) sometimes even overwhelm real data transmission when quantity of user is large, which leads the network and unscalable. In this work, we address the problem with adaptive location-based CSI feedback compression (LFC), LFC utilizes location, the most influential factor of beamforming, and enables users in a group with correlative location sharing the CSI feedback matrix, which makes the MU-MIMO system energy sufficient and scalable. The simulation result shows that LFC could achieve higher throughput than traditional scheme and latest works.