Leveraging Location Information for RIS-aided mmWave MIMO Communications

TL;DR

This paper introduces a method that uses external location data to improve beam alignment and channel estimation in RIS-aided mmWave MIMO systems, leading to faster and more accurate communication setup.

Contribution

It proposes a practical atomic norm minimization-based channel estimation technique that outperforms standard beam alignment in accuracy and spectral efficiency.

Findings

Improved channel estimation accuracy over standard methods.

Faster beam alignment process with less candidate beams.

Enhanced spectrum efficiency with the proposed method.

Abstract

Location information offered by external positioning systems, e.g., satellite navigation, can be used as prior information in the process of beam alignment and channel parameter estimation for reconfigurable intelligent surface (RIS)-aided millimeter wave (mmWave) multiple-input multiple-output networks. Benefiting from the availability of such prior information, albeit imperfect, the beam alignment and channel parameter estimation processes can be significantly accelerated with less candidate beams explored at all the terminals. We propose a practical channel parameter estimation method via atomic norm minimization, which outperforms the standard beam alignment in terms of both the mean square error and the effective spectrum efficiency for the same training overhead.