# Massive MIMO in 5G: How Beamforming, Codebooks, and Feedback Enable Larger Arrays

arXiv: https://arxiv.org/abs/2301.13390 · HTML: https://mlsanity.com/paper/2301.13390/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 31 Jan 2023.

## Built on by (most cited first, 5 of 5)

- [LinFormer: A Linear-based Lightweight Transformer Architecture For Time-Aware MIMO Channel Prediction](https://mlsanity.com/paper/2410.21351/) (2024)
- [Hierarchical ML Codebook Design for Extreme MIMO Beam Management](https://mlsanity.com/paper/2312.02178/) (2023)
- [Neural Codebook Design for Network Beam Management](https://mlsanity.com/paper/2403.03053/) (2024)
- [Heterogeneity-agnostic AI/ML-assisted beam selection for multi-panel arrays](https://mlsanity.com/paper/2602.18678/) (2026)
- [Semantic CSI Feedback for Beam Selection: When Task-Aware Embeddings from Sparse Pilots Outperform Full-Bandwidth Reconstruction](https://mlsanity.com/paper/2609.18368/) (2026)

## Abstract (arXiv)

Massive multiple-input multiple-output (MIMO) is an important technology in fifth generation (5G) cellular networks and beyond. To help design the beamforming at the base station, 5G has introduced new support in the form of flexible feedback and configurable antenna array geometries. In this article, we present an overview of MIMO throughout the mobile standards, highlight the new beam-based feedback system in 5G NR, and describe how this feedback system enables massive MIMO through beam management. Finally, we conclude with challenges related to massive MIMO in 5G.