Parametric Schemes for Prediction of Wideband MIMO Wireless Channels

TL;DR

This paper develops parametric extrapolation methods for predicting future states of wideband MIMO channels using advanced ESPRIT-based algorithms, aiming to improve feedback efficiency in MIMO-OFDM systems.

Contribution

It introduces three novel channel predictors based on 4D, 3D, and 2D ESPRIT extensions and derives a theoretical bound on prediction error for wideband MIMO channels.

Findings

Proposed predictors outperform existing methods in simulations.

The derived error bound closely matches simulation results.

Predictors effectively estimate future channel states under various conditions.

Abstract

Information on the future state of time varying frequency selective channels can significantly enhance the effectiveness of feedback in adaptive and limited feedback MIMO-OFDM systems. This paper investigates the parametric extrapolation of wideband MIMO channels using variations of the double directional MIMO model. We propose three predictors which estimate parameters of the channel using 4D, 3D and 2D extensions of the ESPRIT algorithm and predict future states of the channel using the models. Furthermore, using the vector formulation of the Cramer Rao lower bound for functions of parameters, we derive a bound on the prediction error in wideband MIMO channels. Numerical simulations are used to evaluate the performance of the proposed algorithms under different channel and transmission conditions, and a comparison is made with the derived error bound.