From Semantic to Token Communication: The Next Paradigm for Large-Model-Driven 6G Intelligent Connectivity

📅 2026-09-09
📈 Citations: 0
Influential: 0
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🤖 AI Summary
论文探讨了从语义通信到令牌通信的转变,以应对6G网络需求,提出使用令牌作为统一的语义处理单元,增强互操作性和系统设计。
📝 Abstract
The ambitious requirements of sixth-generation (6G) networks are driving communication systems from reliable bit delivery toward meaning-aware and task-oriented connectivity. Large models (LMs), with strong multimodal understanding and generation capabilities, have accelerated this shift and made semantic communication (SemCom) increasingly practical. Yet current LM-driven SemCom remains fragmented: semantic representations are typically tied to specific modalities, models, or tasks. While the bit provides a universal unit for digital transport, there is still no analogous unit for representing and processing semantics, which limits interoperability, theoretical unification, and scalable system design. We argue that tokens provide a natural candidate for this missing abstraction. Two trends support this: unified multimodal LMs now encode text, images, audio, video, and robot actions in one token space, while distributed LM inference already generates substantial token-level traffic through expert routing, cache transfer, and speculative decoding. Token communication (TokenCom) emerges by unifying these trends, using the LM's native processing unit as a communication abstraction above the bit level and enabling importance assignment, error handling, and resource allocation directly at token granularity. This survey traces the evolution from LM-driven SemCom to TokenCom. We review three major directions of LM-driven SemCom: source-centric semantic coding, channel semantics for physical-layer tasks, and collaborative edge-device intelligence. We then examine the token abstraction, the transmission techniques it requires, and two emerging paradigms, namely TokenCom for LM services and for embodied and agentic intelligence. Finally, we identify open challenges toward unified, scalable, and AI-native 6G communication systems.
Problem

Research questions and friction points this paper is trying to address.

semantic communication
large models
interoperability
token abstraction
6G networks
Innovation

Methods, ideas, or system contributions that make the work stand out.

Token Communication
Semantic Communication
Large Models
6G Networks
Multimodal Understanding
Yu Ma
Yu Ma
Indiana University
Computer Science
Zhen Gao
Zhen Gao
Beijing Institute of Technology
Generative AI6GMIMO communicationsIoT edge computingLarge Model
Li Qiao
Li Qiao
Beijing Institute of Technology
Wireless Communications,Signal Processing,Machine Learning
Xiaoyuan Zhang
Xiaoyuan Zhang
Peking University
Multi-Agent LearningReinforcement Learning
Mahdi Boloursaz Mashhadi
Mahdi Boloursaz Mashhadi
Lecturer (Assistant Professor) at University of Surrey
Wireless CommunicationsSignal ProcessingMachine Learning
Yin Xu
Yin Xu
Beijing Jiaotong University
Power Grid ResilienceElectricity-Transportation Integrated SystemPower System High-Performance Simulation
Wenjun Xu
Wenjun Xu
Peng Cheng Laboratory
machine learningreinforcement learningflexible/soft robot
X
Xiaodong Xu
State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China
Kaibin Huang
Kaibin Huang
Professor and Dept.Head, University of Hong Kong; NAI Fellow; IEEE Fellow; Highly Cited Researcher
Machine LearningMobile Edge ComputingWireless CommunicationsWireless Power Transfer
Jiangzhou Wang
Jiangzhou Wang
Professor, University of Kent
Mobile Communications
R
Rahim Tafazolli
5G/6G Innovation Centre (5G/6GIC), Institute for Communication Systems, University of Surrey, Guildford GU2 7XH, UK
S
Sheng Chen
School of Electronics and Computer Science, University of Southampton, Southampton SO17 1BJ, UK
T
Tony Q. S. Quek
Information Systems Technology and Design Pillar, Singapore University of Technology and Design, Singapore 487372, Singapore
Ping Zhang
Ping Zhang
Beijing University of Posts and Telecommunications
next-generation mobile networkssemantic communicationsintellicise communication system