CSI Transfer From Sub-6G to mmWave: Reduced-Overhead Multi-User Hybrid Beamforming

TL;DR

A Sub-6G information Aided Multi-User Hybrid Beamforming (SA-MUHBF) framework is proposed, avoiding excessive use of pilots at mmWave and achieves superior spectrum efficiency over state-of-the-art benchmarks.

Abstract

Hybrid beamforming is vital in modern wireless systems, especially for massive MIMO and millimeter-wave (mmWave) deployments, offering efficient directional transmission with reduced hardware complexity. However, effective beamforming in multi-user scenarios relies heavily on accurate channel state information, the acquisition of which often requires significant pilot overhead, degrading system performance. To address this and inspired by the spatial congruence between sub-6GHz (sub-6G) and mmWave channels, we propose a Sub-6G information Aided Multi-User Hybrid Beamforming (SA-MUHBF) framework, avoiding excessive use of pilots at mmWave. SA-MUHBF employs a convolutional neural network to predict mmWave beamspace from sub-6G channel estimate, followed by a novel multi-layer graph neural network for analog beam selection and a linear minimum mean-square error algorithm for digital beamforming. Numerical results demonstrate that SA-MUHBF efficiently predicts the mmWave beamspace representation and achieves superior spectrum efficiency over state-of-the-art benchmarks. Moreover, SA-MUHBF demonstrates robust performance across varied sub-6G system configurations and exhibits strong generalization to unseen scenarios.

Figures (13)

• Figure 1: Illustration of (a) the dual-band communication system and (b) the beamforming architectures of mmWave system and sub-6G system.
• Figure 2: Normalized beamspace representation of sub-6G channel and mmWave channel.
• Figure 3: The overall design of SA-MUHBF framework.
• Figure 4: An illustration of the mmWave beamspace representation prediction stage.
• Figure 5: Illustration of the interference graph.