Hierarchical Beam Alignment for Millimeter-Wave Communication Systems: A Deep Learning Approach

by   Junyi Yang, et al.

Fast and precise beam alignment is crucial for high-quality data transmission in millimeter-wave (mmWave) communication systems, where large-scale antenna arrays are utilized to overcome the severe propagation loss. To tackle the challenging problem, we propose a novel deep learning-based hierarchical beam alignment method for both multiple-input single-output (MISO) and multiple-input multiple-output (MIMO) systems, which learns two tiers of probing codebooks (PCs) and uses their measurements to predict the optimal beam in a coarse-to-fine search manner. Specifically, a hierarchical beam alignment network (HBAN) is developed for MISO systems, which first performs coarse channel measurement using a tier-1 PC, then selects a tier-2 PC for fine channel measurement, and finally predicts the optimal beam based on both coarse and fine measurements. The propounded HBAN is trained in two steps: the tier-1 PC and the tier-2 PC selector are first trained jointly, followed by the joint training of all the tier-2 PCs and beam predictors. Furthermore, an HBAN for MIMO systems is proposed to directly predict the optimal beam pair without performing beam alignment individually at the transmitter and receiver. Numerical results demonstrate that the proposed HBANs are superior to the state-of-art methods in both alignment accuracy and signaling overhead reduction.


page 1

page 9

page 12


Enhanced Beam Alignment for Millimeter Wave MIMO Systems: A Kolmogorov Model

We present an enhancement to the problem of beam alignment in millimeter...

Near-Field Hierarchical Beam Management for RIS-Enabled Millimeter Wave Multi-Antenna Systems

In this paper, we present a low overhead beam management approach for ne...

Continuous Beam Alignment for Mobile MIMO

Millimeter-wave transceivers use large antenna arrays to form narrow hig...

Grid-Free MIMO Beam Alignment through Site-Specific Deep Learning

Beam alignment is a critical bottleneck in millimeter wave (mmWave) comm...

Active Sensing for Two-Sided Beam Alignment and Reflection Design Using Ping-Pong Pilots

Beam alignment is an important task for millimeter-wave (mmWave) communi...

Real-Time Millimeter-Wave MIMO Channel Sounder for Dynamic Directional Measurements

In this paper, we present a novel real-time multiple-input-multiple-outp...

Deep Learning Beam Optimization in Millimeter-Wave Communication Systems

We propose a method that combines fixed point algorithms with a neural n...

Please sign up or login with your details

Forgot password? Click here to reset