Spatial Covariance Estimation for Millimeter Wave Hybrid Systems using Out-of-Band Information

TL;DR

This paper introduces methods to leverage sub-6 GHz channel covariance as out-of-band information to improve millimeter wave link configuration, significantly reducing training overhead in high mobility scenarios.

Contribution

It proposes a novel out-of-band covariance translation and aided estimation approach for mmWave systems using sub-6 GHz data, enhancing link configuration efficiency.

Findings

Covariance translation eliminates in-band training.

Out-of-band aided estimation reduces training overhead.

Methods improve link configuration in high mobility scenarios.

Abstract

In high mobility applications of millimeter wave (mmWave) communications, e.g., vehicle-to-everything communication and next-generation cellular communication, frequent link configuration can be a source of significant overhead. We use the sub-6 GHz channel covariance as an out-of-band side information for mmWave link configuration. Assuming: (i) a fully digital architecture at sub-6 GHz; and (ii) a hybrid analog-digital architecture at mmWave, we propose an out-of-band covariance translation approach and an out-of-band aided compressed covariance estimation approach. For covariance translation, we estimate the parameters of sub-6 GHz covariance and use them in theoretical expressions of covariance matrices to predict the mmWave covariance. For out-of-band aided covariance estimation, we use weighted sparse signal recovery to incorporate out-of-band information in compressed covariance estimation. The out-of-band covariance translation eliminates the in-band training completely, whereas out-of-band aided covariance estimation relies on in-band as well as out-of-band training. We also analyze the loss in the signal-to-noise ratio due to an imperfect estimate of the covariance. The simulation results show that the proposed covariance estimation strategies can reduce the training overhead compared to the in-band only covariance estimation.