Channel state information feedback method for Massive MIMO OFDM

MIMO-OFDM with a massive number of transmit antennas (Massive MIMO-OFDM) promises to increase the spectrum efficiency or reduce the transmission energy per bit. The performance of Massive MIMO-OFDM is strongly influenced by the method used to estimate the channel state information (CSI) at the transmitter. Given the massive number of transmit antennas, the many training frames needed for CSI estimation decreases MAC efficiency and increases the cost of estimating CSI at a user station (STA). This paper presents a CSI estimation scheme that reduces the training frame length by using a rank enhancement pilot design. This design assigns a different CSI estimation weight to each subcarrier. The STAs feed unitary matrices, that are obtained by multiplying the left and right singular vectors, back to the AP. The proposed CSI method enables the AP to obtain accurate CSI for limited signal spaces and less-accurate CSI for wider signal spaces for setting data transmission weights and CSI estimation weights, respectively. Simulations of an IEEE802.11n channel show that the proposed CSI estimation scheme with very short training frames obtains greater than 95% of the achievable bit rate of a full CSI estimation in Massive MIMO-OFDM systems with 32 transmit antennas, 2 receive antennas, and 3 STAs.