# Beam Training based on Dynamic Hierarchical Codebook for Millimeter Wave Massive MIMO

## TL;DR

This paper introduces a dynamic hierarchical codebook approach for millimeter wave massive MIMO beam training, which adapts based on estimated multi-path components to improve detection success rates.

## Contribution

The paper proposes a novel generalized design for dynamic hierarchical codebooks that update according to estimated MPCs, enhancing beam training efficiency.

## Key findings

- Outperforms existing methods in success detection rate
- Effective in dynamically updating codebooks based on MPC estimates
- Verified through simulation results

## Abstract

Beam training based on hierarchical codebook for millimeter wave (mmWave) massive MIMO is investigated. Unlike the existing work using the same hierarchical codebook to estimate different multi-path components (MPCs), dynamic hierarchical codebooks which are updated according to the estimated MPCs are adopted. Firstly, a generalized hierarchical codebook design method is proposed. Then based on this method, a beam training method which dynamically updates the hierarchical codebook by removing the contribution of the estimated MPCs from the codebook is proposed. Simulation results verify the effectiveness of our method and show that the proposed method outperforms the existing ones in terms of the success detection rate of beam training.