Channel Fingerprint Based Beam Tracking for Millimeter Wave Communications

TL;DR

This paper introduces a channel fingerprint-based beam tracking scheme for mmWave communications that reduces training overhead and improves beamforming performance by leveraging statistical gain-location mappings.

Contribution

It presents a novel beam tracking method using a channel fingerprint database to efficiently estimate beam gains without exhaustive training.

Findings

Significant performance improvements over existing schemes

Reduced training overhead in beam tracking

Effective user movement estimation using channel fingerprints

Abstract

Beamforming structures with fixed beam codebooks provide economical solutions for millimeter wave (mmWave) communications due to the low hardware cost. However, the training overhead to search for the optimal beamforming configuration is proportional to the codebook size. To improve the efficiency of beam tracking, we propose a beam tracking scheme based on the channel fingerprint database, which comprises mappings between statistical beamforming gains and user locations. The scheme tracks user movement by utilizing the trained beam configurations and estimating the gains of beam configurations that are not trained. Simulations show that the proposed scheme achieves significant beamforming performance gains over existing beam tracking schemes.