Beam Management

Beam management optimizes the selection and maintenance of optimal transmit and receive beam pairs in wireless communication systems, aiming to maximize data throughput and minimize interference. Current research heavily utilizes machine learning, employing neural networks (including autoencoders and recurrent networks), random forests, and generative adversarial networks to improve codebook design, predict optimal beams, and enhance beam alignment, often incorporating environmental information like location and orientation. These advancements are crucial for enabling efficient operation of large antenna arrays in 5G and beyond, particularly in millimeter-wave systems and ultra-dense networks, leading to improved spectral efficiency and reduced latency.

Papers

October 22, 2024

Multi-Modal Transformer and Reinforcement Learning-based Beam Management
Mohammad Ghassemi, Han Zhang, Ali Afana, Akram Bin Sediq, Melike Erol-Kantarci
Positive Reinforcement Multi Modal Transformer Beam Prediction Beam Management Optimal Beam

March 5, 2024

Neural Codebook Design for Network Beam Management
Ryan M. Dreifuerst, Robert W. Heath
Codebook Learning Antenna Array Beam Management

December 30, 2023

Machine Learning (ML)-assisted Beam Management in millimeter (mm)Wave Distributed Multiple Input Multiple Output (D-MIMO) systems
Karthik R M, Dhiraj Nagaraja Hegde, Muris Sarajlic, Abhishek Sarkar
Machine Learning Conditional Generative Adversarial Network C Gan Multiple Input Multiple Output mmWave Signal Beam Prediction Wireless Node Beam Management

November 24, 2023

Hierarchical ML Codebook Design for Extreme MIMO Beam Management
Ryan M. Dreifuerst, Robert W. Heath
Multiple Input Multiple Output Adaptive Beamforming Codebook Learning Antenna Array Beam Management Beam Selection

May 23, 2023

Trend-Based SAC Beam Control Method with Zero-Shot in Superconducting Linear Accelerator
Xiaolong Chen, Xin Qi, Chunguang Su, Yuan He, Zhijun Wang, Kunxiang Sun, Chao Jin, Weilong Chen, Shuhui Liu, Xiaoying Zhao, Duanyang Jia, Man Yi
Proton Beam Beam Prediction Particle Accelerator Beam Management

March 21, 2023

Beam Management Driven by Radio Environment Maps in O-RAN Architecture
Marcin Hoffmann, Pawel Kryszkiewicz
Multiple Input Multiple Output Open Radio Access Network Radio Map RAN Architecture Beam Management

February 17, 2023

Deep Reinforcement Learning for mmWave Initial Beam Alignment
Daniel Tandler, Sebastian Dörner, Marc Gauger, Stephan ten Brink
Deep Reinforcement Learning Proximal Policy Optimization Deep Reinforcement Beam Management

October 4, 2022

Beam Management in Ultra-dense mmWave Network via Federated Reinforcement Learning: An Intelligent and Secure Approach
Qing Xue, Yi-Jing Liu, Yao Sun, Jian Wang, Li Yan, Gang Feng, Shaodan Ma
mmWave Signal Federated Reinforcement Learning Secure Approach Ultra Dense Network Beam Management mmWave Network

July 28, 2022

Bayesian Optimization-Based Beam Alignment for MmWave MIMO Communication Systems
Songjie Yang, Baojuan Liu, Zhiqin Hong, Zhongpei Zhang
Bayesian Perspective Millimeter Wave Beam Management Optimal Beam Beam Alignment

April 12, 2022

Massive MIMO Beam Management in Sub-6 GHz 5G NR
Ryan M. Dreifuerst, Robert W. Heath, Ali Yazdan
Multiple Input Multiple Output Codebook Learning Massive MIMO G Wireless Proton Beam Beam Management

February 4, 2022

Beam Management with Orientation and RSRP using Deep Learning for Beyond 5G Systems
Khuong N. Nguyen, Anum Ali, Jianhua Mo, Boon Loong Ng, Vutha Va, Jianzhong Charlie Zhang
Deep Learning Inertial Measurement Unit G Wireless Beam Prediction Head Orientation Onboard Sensor Reference Signal Received Power Beam Management