Training Protocols for Multi-User MIMO Wireless LANs

In this paper, we investigate the training problem of wireless local area networks (WLANs) with downlink multi-user multiple input multiple output (DL MU MIMO) capability. We extend the 802.11 MAC protocol and propose a few training protocols at the MAC layer to support DL MU MIMO. We provide a capacity analysis based on measurement results from an 802.11n systems, evaluate the overhead of these training protocols, and compare the performance of DL MU MIMO with that of a beam-forming (BF) based approach. Through simulation studies, we find that at high SNR and with implicit training, the DL MU MIMO mechanism provides significant performance gain over the BF based approach. Furthermore, our capacity analysis and simulation study also show that it is critical to define appropriate training intervals based on antenna configuration, channel mobility, and CSI feedback overhead.