Data to 14 Oct 2026

Toward a 6G AI-Native Air Interface

arXiv 2012.08285 ↗First posted 15 Dec 2020cs.NI cs.AI cs.ITcited by 55

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Abstract (arXiv)

Each generation of cellular communication systems is marked by a defining disruptive technology of its time, such as orthogonal frequency division multiplexing (OFDM) for 4G or Massive multiple-input multiple-output (MIMO) for 5G. Since artificial intelligence (AI) is the defining technology of our time, it is natural to ask what role it could play for 6G. While it is clear that 6G must cater to the needs of large distributed learning systems, it is less certain if AI will play a defining role in the design of 6G itself. The goal of this article is to paint a vision of a new air interface which is partially designed by AI to enable optimized communication schemes for any hardware, radio environment, and application.

Key facts. Cited by 55 papers in the map (data through 14 Oct 2026). First posted on arXiv 15 Dec 2020.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 6; 2022: 9; 2023: 11; 2024: 5; 2025: 18; 2026: 6.

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2022Sionna: An Open-Source Library for Next-Generation Physical Layer Researchcited by 145
2021Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and Applicationscited by 97
2021Semantic Communications: Principles and Challengescited by 91
2022Less Data, More Knowledge: Building Next Generation Semantic Communication Networkscited by 62
2023Sionna RT: Differentiable Ray Tracing for Radio Propagation Modelingcited by 62
2022Overview of Deep Learning-based CSI Feedback in Massive MIMO Systemscited by 37
2024Artificial General Intelligence (AGI)-Native Wireless Systems: A Journey Beyond 6Gcited by 31
2022Robust Information Bottleneck for Task-Oriented Communication with Digital Modulationcited by 29
2023Learning Radio Environments by Differentiable Ray Tracingcited by 23
2023AI-native Interconnect Framework for Integration of Large Language Model Technologies in 6G Systemscited by 19
2021The Emergence of Wireless MAC Protocols with Multi-Agent Reinforcement Learningcited by 15
2025AI-RAN: Transforming RAN with AI-driven Computing Infrastructurecited by 14

38 more

2025A Wireless Foundation Model for Multi-Task Predictioncited by 12
2022Towards Semantic Communication Protocols: A Probabilistic Logic Perspectivecited by 10
2023Message Passing Meets Graph Neural Networks: A New Paradigm for Massive MIMO Systemscited by 8
2023How to Evaluate Semantic Communications for Images with ViTScore Metric?cited by 6
2022AI for CSI Feedback Enhancement in 5G-Advancedcited by 4
2022The Internet of Senses: Building on Semantic Communications and Edge Intelligencecited by 4
2023Probabilistic Constellation Shaping With Denoising Diffusion Probabilistic Models: A Novel Approachcited by 4
2024Multiple Access in the Era of Distributed Computing and Edge Intelligencecited by 4
2024The Energy Cost of Artificial Intelligence Lifecycle in Communication Networkscited by 4
2021Few-Shot Domain Adaptation For End-to-End Communicationcited by 3
2021Learning OFDM Waveforms with PAPR and ACLR Constraintscited by 3
2025Adaptive End-to-End Transceiver Design for NextG Pilot-Free and CP-Free Wireless Systemscited by 3
2022Federated Spatial Reuse Optimization in Next-Generation Decentralized IEEE 802.11 WLANscited by 2
2023Generative AI-Based Probabilistic Constellation Shaping With Diffusion Modelscited by 2
2024Interpreting Deep Neural Network-Based Receiver Under Varying Signal-To-Noise Ratioscited by 2
2025LLM-Based Emulation of the Radio Resource Control Layer: Towards AI-Native RAN Protocolscited by 2
2022DUIDD: Deep-Unfolded Interleaved Detection and Decoding for MIMO Wireless Systemscited by 1
2023SICNN: Soft Interference Cancellation Inspired Neural Network Equalizerscited by 1
2023Magmaw: Modality-Agnostic Adversarial Attacks on Machine Learning-Based Wireless Communication Systemscited by 1
2023Auto-CsiNet: Scenario-customized Automatic Neural Network Architecture Generation for Massive MIMO CSI Feedbackcited by 1
2023Deep Learning-Based Pilotless Spatial Multiplexingcited by 1
2025Understanding 6G through Language Models: A Case Study on LLM-aided Structured Entity Extraction in Telecom Domaincited by 1
2025A Survey on the Role of Artificial Intelligence and Machine Learning in 6G-V2X Applicationscited by 1
2025HELENA: High-Efficiency Learning-based channel Estimation using dual Neural Attentioncited by 1
2025Demonstrating Interoperable Channel State Feedback Compression with Machine Learningcited by 1
2025Towards AI-Native RAN: An Operator's Perspective of 6G Day 1 Standardizationcited by 1
2025ATLAS: AI-Native Receiver Test-and-Measurement by Leveraging AI-Guided Searchcited by 1
2021Blind Coherent Preamble Detection via Neural Networkscited by 0
2024Integrating Semantic Communication and Human Decision-Making into an End-to-End Sensing-Decision Frameworkcited by 0
2025VERITAS: Verifying the Performance of AI-native Transceiver Actions in Base-Stationscited by 0
2025Decision Feedback In-Context Learning for Wireless Symbol Detectioncited by 0
2025A Representation Learning Approach to Feature Drift Detection in Wireless Networkscited by 0
2025Out-of-Distribution Detection via Channelwise Feature Aggregation in Neural Network-Based Receiverscited by 0
2025Way to Build Native AI-driven 6G Air Interface: Principles, Roadmap, and Outlookcited by 0
2025Energy-Aware 6G Network Design: A Surveycited by 0
2025Efficient Quantization-Aware Neural Receivers: Beyond Post-Training Quantizationcited by 0
2025Targeted Fine-Tuning of DNN-Based Receivers via Influence Functionscited by 0
2026Studying the Role of Synthetic Data for Machine Learning-based Wireless Networks Traffic Forecastingcited by 0

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