# Leveraging Location Information for RIS-aided mmWave MIMO Communications

arXiv: https://arxiv.org/abs/2010.14163 · HTML: https://mlsanity.com/paper/2010.14163/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Oct 2020.

## Built on by (most cited first, 3 of 3)

- [Active Sensing for Communications by Learning](https://mlsanity.com/paper/2112.04075/) (2021)
- [Channel Estimation and Hybrid Architectures for RIS-Assisted Communications](https://mlsanity.com/paper/2104.07115/) (2021)
- [Beyond 5G RIS mmWave Systems: Where Communication and Localization Meet](https://mlsanity.com/paper/2109.07729/) (2021)

## Abstract (arXiv)

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.