AI Techniques for Integrated Sensing and Communication in Future Networks

Dear Colleagues,

The convergence of sensing and communication functionalities—referred to as integrated sensing and communication (ISAC)—is poised to become a foundational pillar in future wireless networks such as 6G and beyond. By leveraging shared spectrum and hardware resources, ISAC enables systems to simultaneously perceive and connect with the environment, supporting applications ranging from autonomous driving and smart cities to industrial automation. However, the co-design and optimization of sensing and communication introduce significant technical challenges, especially under dynamic, uncertain, and resource-constrained conditions.

This Special Issue aims to explore how artificial intelligence (AI)—including machine learning, deep learning, reinforcement learning, generative AI models, and large-scale foundational models—can address key bottlenecks in ISAC system design, implementation, and deployment. The focus will span AI-driven physical layer design, resource allocation, cross-domain feature extraction, edge intelligence, semantic sensing and communication, and robust adaptation in non-stationary environments.

The scope includes both theoretical and practical contributions across the following domains:

• Large model and generative AI for ISAC;
• Agentic collaborative intelligence for ISAC;
• Multimodal data fusion for ISAC enhancement;
• AI driven MIMO, massive MIMO, and holographic MIMO for ISAC;
• AI driven waveform and beamforming design for ISAC;
• AI driven resource allocation for ISAC;
• Semantic sensing and communication in ISAC system;
• AI driven near-field ISAC signal processing;
• AI driven ISAC for low-altitude economy;
• Deep learning-based spectrum sensing and dynamic spectrum access;
• Environmental adaptation enhancement with AI driven ISAC;
• AI driven interference identification and mitigation;
• Environment mapping and communication-aware perception;
• Experimental testbeds for AI driven ISAC.

This Issue will supplement the existing literature by shifting emphasis from traditional heuristic or model-based approaches toward data-driven, adaptive intelligence for ISAC. While recent works have investigated ISAC frameworks or AI for communication and sensing separately, few have thoroughly examined their integration under a unified AI lens. By bridging this gap, the Special Issue will serve as a timely reference for both academia and industry, offering a holistic view of how AI can unlock the full potential of integrated sensing and communication in next-generation networks.

Dr. Shuhang Zhang
Dr. Haobo Zhang
Dr. Kangjun Liu
Guest Editors

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• artificial intelligence
• integrated sensing and communication
• wireless networks