Tranceiver Design using Linear Precoding in a Multiuser MIMO System with Limited Feedback

TL;DR

This paper presents a novel linear precoding transceiver design for multiuser MIMO systems with limited feedback, improving performance by accounting for channel uncertainties and removing dimensionality constraints.

Contribution

It introduces an end-to-end SMSE transceiver design that incorporates receiver combining, feedback policy, and precoder design with channel uncertainty, and removes dimensionality constraints for multiple data streams per user.

Findings

Outperforms previous limited feedback MU linear transceivers.

Feedback overhead scales linearly with data streams, not antennas.

Analytical insight into bit error rate increase at high SNR when quantization error is ignored.

Abstract

We investigate quantization and feedback of channel state information in a multiuser (MU) multiple input multiple output (MIMO) system. Each user may receive multiple data streams. Our design minimizes the sum mean squared error (SMSE) while accounting for the imperfections in channel state information (CSI) at the transmitter. This paper makes three contributions: first, we provide an end-to-end SMSE transceiver design that incorporates receiver combining, feedback policy and transmit precoder design with channel uncertainty. This enables the proposed transceiver to outperform the previously derived limited feedback MU linear transceivers. Second, we remove dimensionality constraints on the MIMO system, for the scenario with multiple data streams per user, using a combination of maximum expected signal combining (MESC) and minimum MSE receiver. This makes the feedback of each user independent of the others and the resulting feedback overhead scales linearly with the number of data streams instead of the number of receiving antennas. Finally, we analyze SMSE of the proposed algorithm at high signal-to-noise ratio (SNR) and large number of transmit antennas. As an aside, we show analytically why the bit error rate, in the high SNR regime, increases if quantization error is ignored.