Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Channel Estimation for mmWave MIMO using sub-6 GHz Out-of-Band Information

Faruk Pasic, Markus Hofer, Mariam Mussbah, Sebastian Caban, Stefan Schwarz, Thomas Zemen, Christoph F. Mecklenbräuker

TL;DR

The paper addresses the challenge of acquiring accurate CSI for mmWave MIMO links by exploiting sub-6 GHz out-of-band information. It introduces three pilot-aided channel estimation schemes—Translating, Averaging, and Weighting—to fuse sub-6 GHz and mmWave channel information and then employs SVD-based precoding/combining for data transmission. Simulation results show that cross-band fusion can substantially boost spectral efficiency, especially at low SNRs and high K-factors, with the Weighted fusion offering the most robust gains across conditions. This approach enables more reliable mmWave beamforming and communication performance by leveraging cross-band channel correlations without excessive training overhead.

Abstract

Future wireless multiple-input multiple-output (MIMO) communication systems will employ sub-6 GHz and millimeter wave (mmWave) frequency bands working cooperatively. Establishing a MIMO communication link usually relies on estimating channel state information (CSI) which is difficult to acquire at mmWave frequencies due to a low signal-to-noise ratio (SNR). In this paper, we propose three novel methods to estimate mmWave MIMO channels using out-of-band information obtained from the sub-6GHz band. We compare the proposed channel estimation methods with a conventional one utilizing only in-band information. Simulation results show that the proposed methods outperform the conventional mmWave channel estimation method in terms of achievable spectral efficiency, especially at low SNR and high K-factor.

Channel Estimation for mmWave MIMO using sub-6 GHz Out-of-Band Information

TL;DR

The paper addresses the challenge of acquiring accurate CSI for mmWave MIMO links by exploiting sub-6 GHz out-of-band information. It introduces three pilot-aided channel estimation schemes—Translating, Averaging, and Weighting—to fuse sub-6 GHz and mmWave channel information and then employs SVD-based precoding/combining for data transmission. Simulation results show that cross-band fusion can substantially boost spectral efficiency, especially at low SNRs and high K-factors, with the Weighted fusion offering the most robust gains across conditions. This approach enables more reliable mmWave beamforming and communication performance by leveraging cross-band channel correlations without excessive training overhead.

Abstract

Future wireless multiple-input multiple-output (MIMO) communication systems will employ sub-6 GHz and millimeter wave (mmWave) frequency bands working cooperatively. Establishing a MIMO communication link usually relies on estimating channel state information (CSI) which is difficult to acquire at mmWave frequencies due to a low signal-to-noise ratio (SNR). In this paper, we propose three novel methods to estimate mmWave MIMO channels using out-of-band information obtained from the sub-6GHz band. We compare the proposed channel estimation methods with a conventional one utilizing only in-band information. Simulation results show that the proposed methods outperform the conventional mmWave channel estimation method in terms of achievable spectral efficiency, especially at low SNR and high K-factor.
Paper Structure (12 sections, 22 equations, 3 figures, 2 tables)

This paper contains 12 sections, 22 equations, 3 figures, 2 tables.

Table of Contents

  1. Introduction
  2. System Model
  3. Channel Model
  4. Link Establishment
  5. Training Phase
  6. Data Transmission
  7. Channel Estimation Methods
  8. Translating
  9. Averaging
  10. Weighting
  11. Simulation-based Comparison
  12. Conclusion

Figures (3)

  • Figure 1: A multi-band MIMO transmission system with co-located sub-6 GHz and MMW antenna arrays. $\mathbf{H}^{\left( \rm s \right)}$ denotes the sub-6 GHz MIMO channel. $\mathbf{H}^{\left( \rm m \right)}$ denotes the MMW MIMO channel.
  • Figure 2: Pilot symbols at each antenna occupy a certain number of subcarriers such that they do not overlap in the frequency domain.
  • Figure 3: For the TDL-A 4$\times$4 MIMO channel, the proposed weighting method achieves up to 80% higher SE. The small vertical bars within the circular markers indicate the 95% confidence intervals.