Optimized Training and Feedback for MIMO Downlink Channels

TL;DR

This paper optimizes training and feedback strategies in MIMO downlink channels, demonstrating that digital feedback yields higher net rates than analog feedback under certain conditions.

Contribution

It introduces an optimization framework for training and feedback in MIMO channels, comparing analog and digital feedback methods for the first time.

Findings

Digital feedback outperforms analog feedback in net achievable rate.

Optimal training length is similar for both feedback types.

The study provides a practical approach to maximize throughput in MIMO systems.

Abstract

We consider a MIMO fading broadcast channel where channel state information is acquired at user terminals via downlink training and channel feedback is used to provide transmitter channel state information (CSIT) to the base station. The feedback channel (the corresponding uplink) is modeled as an AWGN channel, orthogonal across users. The total bandwidth consumed is the sum of the bandwidth/resources used for downlink training, channel feedback, and data transmission. Assuming that the channel follows a block fading model and that zeroforcing beamforming is used, we optimize the net achievable rate for unquantized (analog) and quantized (digital) channel feedback. The optimal number of downlink training pilots is seen to be essentially the same for both feedback techniques, but digital feedback is shown to provide a larger net rate than analog feedback.