Exploiting Channel Correlations - Simple Interference Alignment Schemes with no CSIT

TL;DR

This paper demonstrates that by exploiting channel correlation structures, interference alignment can be achieved without channel state information at transmitters in various network scenarios, challenging previous beliefs about DoF collapse.

Contribution

It introduces simple linear beamforming schemes that leverage channel correlation to enable interference alignment without CSIT across multiple network models.

Findings

Interference alignment is possible without CSIT using channel correlation.

Linear beamforming schemes achieve alignment with minimal delay.

Total degrees of freedom are preserved despite channel uncertainty.

Abstract

We explore 5 network communication problems where the possibility of interference alignment, and consequently the total number of degrees of freedom (DoF) with channel uncertainty at the transmitters are unknown. These problems share the common property that in each case the best known outer bounds are essentially robust to channel uncertainty and represent the outcome with interference alignment, but the best inner bounds -- in some cases conjectured to be optimal -- predict a total collapse of DoF, thus indicating the infeasibility of interference alignment under channel uncertainty at transmitters. Our main contribution is to show that even with no knowledge of channel coefficient values at the transmitters, the knowledge of the channels' correlation structure can be exploited to achieve interference alignment. In each case, we show that under a staggered block fading model, the transmitters are able to align interference without the knowledge of channel coefficient values. The alignment schemes are based on linear beamforming -- which can be seen as a repetition code over a small number of symbols -- and involve delays of only a few coherence intervals.