The Degrees of Freedom Region of Temporally-Correlated MIMO Networks with Delayed CSIT

TL;DR

This paper fully characterizes the degrees of freedom regions in temporally-correlated MIMO broadcast and interference channels with delayed and imperfect current CSIT, introducing a unified framework that optimally combines outdated and current channel information.

Contribution

It introduces a unified framework for achieving the optimal DoF region in MIMO networks with temporally-correlated channels and delayed CSIT, simplifying the achievability proof process.

Findings

Achieves the entire DoF region with a single scheme by varying power allocation.

Provides a systematic method for proving achievability without checking all corner points.

Characterizes DoF regions as a function of prediction quality indicator.

Abstract

We consider the temporally-correlated Multiple-Input Multiple-Output (MIMO) broadcast channels (BC) and interference channels (IC) where the transmitter(s) has/have (i) delayed channel state information (CSI) obtained from a latency-prone feedback channel as well as (ii) imperfect current CSIT, obtained, e.g., from prediction on the basis of these past channel samples based on the temporal correlation. The degrees of freedom (DoF) regions for the two-user broadcast and interference MIMO networks with general antenna configuration under such conditions are fully characterized, as a function of the prediction quality indicator. Specifically, a simple unified framework is proposed, allowing to attain optimal DoF region for the general antenna configurations and current CSIT qualities. Such a framework builds upon block-Markov encoding with interference quantization, optimally combining the use of both outdated and instantaneous CSIT. A striking feature of our work is that, by varying the power allocation, every point in the DoF region can be achieved with one single scheme. As a result, instead of checking the achievability of every corner point of the outer bound region, as typically done in the literature, we propose a new systematic way to prove the achievability.