6G White Paper on Machine Learning in Wireless Communication Networks
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Abstract (arXiv)
The focus of this white paper is on machine learning (ML) in wireless communications. 6G wireless communication networks will be the backbone of the digital transformation of societies by providing ubiquitous, reliable, and near-instant wireless connectivity for humans and machines. Recent advances in ML research has led enable a wide range of novel technologies such as self-driving vehicles and voice assistants. Such innovation is possible as a result of the availability of advanced ML models, large datasets, and high computational power. On the other hand, the ever-increasing demand for connectivity will require a lot of innovation in 6G wireless networks, and ML tools will play a major role in solving problems in the wireless domain. In this paper, we provide an overview of the vision of how ML will impact the wireless communication systems. We first give an overview of the ML methods that have the highest potential to be used in wireless networks. Then, we discuss the problems that can be solved by using ML in various layers of the network such as the physical layer, medium access layer, and application layer. Zero-touch optimization of wireless networks using ML is another interesting aspect that is discussed in this paper. Finally, at the end of each section, important research questions that the section aims to answer are presented.
Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). First posted on arXiv 28 Apr 2020.
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Citing papers per year: 2021: 3; 2022: 2; 2023: 8; 2024: 0; 2025: 1.
14 papers.
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- 2023Holistic Network Virtualization and Pervasive Network Intelligence for 6Gcited by 14
- 2023Wireless End-to-End Image Transmission System using Semantic Communicationscited by 14
- 2022Multi-Edge Server-Assisted Dynamic Federated Learning with an Optimized Floating Aggregation Pointcited by 10
- 2023Conditional Denoising Diffusion Probabilistic Models for Data Reconstruction Enhancement in Wireless Communicationscited by 10
- 2021IoT Security: Botnet detection in IoT using Machine learningcited by 6
- 2023Optimizing Multicarrier Multiantenna Systems for LoS Channel Chartingcited by 5
- 2022The Adversarial Security Mitigations of mmWave Beamforming Prediction Models using Defensive Distillation and Adversarial Retrainingcited by 3
- 2023Generative AI-Based Probabilistic Constellation Shaping With Diffusion Modelscited by 2
- 2021Event-Driven Source Traffic Prediction in Machine-Type Communications Using LSTM Networkscited by 1
- 2021Deep Learning-Based Active User Detection for Grant-free SCMA Systemscited by 1
- 2023Outage Performance and Novel Loss Function for an ML-Assisted Resource Allocation: An Exact Analytical Frameworkcited by 1
- 2023Learning-Based Latency-Constrained Fronthaul Compression Optimization in C-RANcited by 1
- 2025The Role, Trends, and Applications of Machine Learning in Undersea Communication: A Bangladesh Perspective1 Mar 2025
- 2023Generative AI-Based Probabilistic Constellation Shaping With Diffusion Models15 Nov 2023
- 2023Learning-Based Latency-Constrained Fronthaul Compression Optimization in C-RAN7 Nov 2023
- 2023Conditional Denoising Diffusion Probabilistic Models for Data Reconstruction Enhancement in Wireless Communications30 Oct 2023
- 2023Optimizing Multicarrier Multiantenna Systems for LoS Channel Charting28 Sep 2023
- 2023Denoising Diffusion Probabilistic Models for Hardware-Impaired Communications15 Sep 2023
- 2023Outage Performance and Novel Loss Function for an ML-Assisted Resource Allocation: An Exact Analytical Framework16 May 2023
- 2023Wireless End-to-End Image Transmission System using Semantic Communications27 Feb 2023
- 2023Holistic Network Virtualization and Pervasive Network Intelligence for 6G2 Jan 2023
- 2022Multi-Edge Server-Assisted Dynamic Federated Learning with an Optimized Floating Aggregation Point26 Mar 2022
- 2022The Adversarial Security Mitigations of mmWave Beamforming Prediction Models using Defensive Distillation and Adversarial Retraining16 Feb 2022
- 2021Deep Learning-Based Active User Detection for Grant-free SCMA Systems21 Jun 2021
- 2023Conditional Denoising Diffusion Probabilistic Models for Data Reconstruction Enhancement in Wireless Communicationscited by 10
- 2023Generative AI-Based Probabilistic Constellation Shaping With Diffusion Modelscited by 2
- 2023Denoising Diffusion Probabilistic Models for Hardware-Impaired Communicationscited by 0
- 2023Generative AI-Based Probabilistic Constellation Shaping With Diffusion Models15 Nov 2023
- 2023Conditional Denoising Diffusion Probabilistic Models for Data Reconstruction Enhancement in Wireless Communications30 Oct 2023
- 2023Denoising Diffusion Probabilistic Models for Hardware-Impaired Communications15 Sep 2023
- 2023Holistic Network Virtualization and Pervasive Network Intelligence for 6Gcited by 14
- 2023Wireless End-to-End Image Transmission System using Semantic Communicationscited by 14
- 2022Multi-Edge Server-Assisted Dynamic Federated Learning with an Optimized Floating Aggregation Pointcited by 10
- 2021IoT Security: Botnet detection in IoT using Machine learningcited by 6
- 2023Optimizing Multicarrier Multiantenna Systems for LoS Channel Chartingcited by 5
- 2022The Adversarial Security Mitigations of mmWave Beamforming Prediction Models using Defensive Distillation and Adversarial Retrainingcited by 3
- 2021Event-Driven Source Traffic Prediction in Machine-Type Communications Using LSTM Networkscited by 1
- 2021Deep Learning-Based Active User Detection for Grant-free SCMA Systemscited by 1
- 2023Outage Performance and Novel Loss Function for an ML-Assisted Resource Allocation: An Exact Analytical Frameworkcited by 1
- 2023Learning-Based Latency-Constrained Fronthaul Compression Optimization in C-RANcited by 1
- 2025The Role, Trends, and Applications of Machine Learning in Undersea Communication: A Bangladesh Perspectivecited by 1
- 2025The Role, Trends, and Applications of Machine Learning in Undersea Communication: A Bangladesh Perspective1 Mar 2025
- 2023Learning-Based Latency-Constrained Fronthaul Compression Optimization in C-RAN7 Nov 2023
- 2023Optimizing Multicarrier Multiantenna Systems for LoS Channel Charting28 Sep 2023
- 2023Outage Performance and Novel Loss Function for an ML-Assisted Resource Allocation: An Exact Analytical Framework16 May 2023
- 2023Wireless End-to-End Image Transmission System using Semantic Communications27 Feb 2023
- 2023Holistic Network Virtualization and Pervasive Network Intelligence for 6G2 Jan 2023
- 2022Multi-Edge Server-Assisted Dynamic Federated Learning with an Optimized Floating Aggregation Point26 Mar 2022
- 2022The Adversarial Security Mitigations of mmWave Beamforming Prediction Models using Defensive Distillation and Adversarial Retraining16 Feb 2022
- 2021Deep Learning-Based Active User Detection for Grant-free SCMA Systems21 Jun 2021
- 2021IoT Security: Botnet detection in IoT using Machine learning6 Apr 2021
- 2021Event-Driven Source Traffic Prediction in Machine-Type Communications Using LSTM Networks12 Jan 2021