Adaptive Feedback Compression For MIMO Networks

Abstract

MIMO beamforming technology can scale wireless data rate proportionally with the number of antennas. However, the overhead induced by receivers' CSI (channel state information) feedback scales at a higher rate. In this paper, we address this fundamental tradeoff with Adaptive Feedback Compression (AFC). AFC quantizes or compresses CSI from 3 dimensions --- time, frequency and numerical values, and adapts the intensity of compression according to channel profile. This simple principle faces many practical challenges, e.g., a huge search space for adaption, estimation or prediction of the impact of compression on network throughput, and the coupling of different users in multi-user MIMO networks. AFC meets these challenges using a novel cross-layer adaptation metric, a metric extracted from 802.11 packet preambles, and uses it to guide the selection of compression intensity, so as to balance the tradeoff between overhead reduction and capacity loss (due to compression). We have implemented AFC on a software radio testbed. Our experiments show that AFC can outperform alternative approaches in a variety of radio environments.