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The sixth generation (6G) mobile communication network is envisioned to be artificial intelligence (AI)-native, where AI is no longer an auxiliary tool but an integral part of the network design, operation, and service provisioning, deeply embedded across all layers of wireless communication systems. Wireless foundation models, inspired by the breakthroughs of large AI models in natural language processing, vision, and multi-modal reasoning, open up new opportunities for enabling ubiquitous intelligence in 6G and beyond. By leveraging their cognitive abilities in perception and reasoning, wireless foundation models can rapidly adapt to unforeseen scenarios, simulate complex communication environments, and enable personalized and autonomous wireless services. This paradigm shift from “AI for communications” to “AI-native communications” has the potential to revolutionize the design and operation of future wireless systems.
This Special Issue seeks to bring together leading researchers and practitioners from academia and industry to explore the signal processing foundations, architectures, and algorithmic methodologies required for the design, development, and deployment of wireless foundation models for AI-native 6G networks and beyond. The Special Issue will solicit original research on following topics, but not limited to:
- Model architecture and pre-training of wireless foundation models
- Representation learning for wireless signals: Bridging foundation models with classical signal processing principles, e.g., time-frequency analysis, statistical signal models, structured or parametric representations
- Diffusion models and generative AI for wireless signal processing
- Multi-modal wireless foundation models
- Efficient model compression for resource-constrained devices
- Large-small AI model collaboration over wireless networks
- Wireless foundation models for the physical layer
- Wireless foundation models for the medium access control layer
- Foundation models for emerging technologies, e.g., XL-MIMO, reconfigurable intelligent surface, and fluid antenna systems
- Foundation models for integrated sensing and communication systems
- Privacy, and security of wireless foundation models
- Implementation and standardization of wireless foundation models
- Datasets, benchmarks, and testbeds for wireless foundation models
- Validation of foundation models via industry-standard testbeds and real-world field trials
- Agentic AI for autonomous wireless network operation
To ensure a rigorous peer-review process, all manuscripts must provide enough detail for reviewers to independently verify the results. In cases where proprietary models are used, a thorough account of the implementation details and evaluation methods is mandatory to validate the claimed contributions.
Submission Guidelines
Prospective authors should follow the instructions given on the IEEE JSTSP webpage and submit their manuscripts via the IEEE Author Portal submission system.
Important Dates
Manuscript Submission: May 15, 2026
First Notification: July 14, 2026
Revised Manuscript Submission: September 1, 2026
Acceptance Notification: October 1, 2026
Final Manuscript Due: October 19, 2026
Planned Publication: December 2026
Guest Editors
Le Liang (Lead GE), Southeast University, China. Email: lliang@seu.edu.cn
Jun Zhang, The Hong Kong University of Science and Technology, Hong Kong. Email: eejzhang@ust.hk
Chan-Byoung Chae, Yonsei University, Korea. Email: cbchae@yonsei.ac.kr
Lu Lu, MediaTek, USA. Email: Lu.Lu@mediatek.com
Shugong Xu, Xi’an Jiaotong-Liverpool University, China. Email: Shugong.Xu@xjtlu.edu.cn
Octavia A. Dobre, Memorial University, Canada. Email: odobre@mun.ca
Geoffrey Ye Li, Imperial College London, UK. Email: geoffrey.li@imperial.ac.uk
