Channel Tracking and Transmit Beamforming With Frugal Feedback

Abstract

Channel state feedback is a serious burden that limits deployment of transmit beamforming systems with many antennas in frequency-division duplex (FDD) mode. Transmit beamforming with limited feedback systems estimate the channel at the receiver and send quantized channel state or beamformer information to the transmitter. A different approach that exploits the spatio-temporal correlation of the channel is proposed here. The transmitter periodically sends a beamformed pilot signal in the downlink, while the receiver quantizes the corresponding received signal and feeds back the bits to the transmitter. Assuming an autoregressive (AR) channel model, Kalman filtering (KF) based on the sign of innovations (SOI) is proposed for channel tracking, and closed-form expressions for the channel estimation mean-squared error (MSE) are derived under certain conditions. For more general channel models, a novel tracking approach is proposed that exploits the quantization bits in a maximum a posteriori (MAP) formulation. Simulations show that close to optimum performance can be attained with only 2 bits per channel dwell time block, even for systems with many transmit antennas. This clears a hurdle for transmit beamforming with many antennas in FDD mode—which was almost impossible with the prior state-of-art.