Two-stage Multi-beam Training for Multiuser Millimeter-Wave Communications

TL;DR

This paper introduces a two-stage multi-beam training approach for multiuser millimeter-wave systems that enhances beam identification accuracy and reduces training overhead by using distinct beam patterns and a cross-validation method.

Contribution

The paper proposes a novel two-stage multi-beam training method with different beam patterns and a cross-validation technique to improve efficiency and accuracy in user angle identification.

Findings

Significantly improves success beam-identification rate.

Reduces or maintains training overhead.

Effective in resolving angular ambiguity.

Abstract

In this letter, we study an efficient multi-beam training method for multiuser millimeter-wave communication systems. Unlike the conventional single-beam training method that relies on exhaustive search, multi-beam training design faces a key challenge in balancing the trade-off between beam training overhead and success beam-identification rate, exacerbated by severe inter-beam interference. To tackle this challenge, we propose a new two-stage multi-beam training method with two distinct multi-beam patterns to enable fast and accurate user angle identification. Specifically, in the first stage, the antenna array is divided into sparse subarrays to generate multiple beams (with high array gains), for identifying candidate user angles. In the second stage, the array is redivided into dense subarrays to generate flexibly steered wide beams, for which a cross-validation method is employed to effectively resolve the remaining angular ambiguity in the first stage. Last, numerical results demonstrate that the proposed method significantly improves the success beam-identification rate compared to existing multi-beam training methods, while retaining or even reducing the required beam training overhead.