6G-ENABLED AI-BASED SENSING AND COMMUNICATION CONVERGENCE: A COMPREHENSIVE SURVEY

Abstract

The sixth generation of wireless networks is seeking to achieve the vision of integrated sensing and communication (ISAC), where wireless systems not only transmit data but also sense the environment. This concept allows for high-resolution mapping of environments, autonomous navigation, and extended reality that is immersive. However, implementing ISAC in 6G networks faces major challenges such as spectrum coexistence, shared hardware, adaptive waveform design, and real-time adaptability in dynamic environments. ISAC-enabled AI and ML applications for intelligent resource allocation, robust channel estimation, adaptive beamforming, and ISAC security fortification make them critical for ISAC. This survey offers a thorough overview on the inclusive backbone technologies like THz communications along with massive multiple input multiple output (MIMO) systems and reconfigurable intelligent surfaces (RIS), as well as the current approaches to ISAC channel modeling such as stochastic, deterministic, and hybrid models. Unique focus is given to AI techniques and deep learning, reinforcement learning, privacy-preserving federated ML and the issues of security and the interventions. This survey looks into practical use cases, existing models, as well as gaps in the research and is intended to be the starting point toward the development of AI-driven ISAC for 6G networks.