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Motivated by the need for increased spectral efficiency and the proliferationof intelligent applications, the sixth-generation (6G) mobile network isanticipated to integrate the dual-functions of communication and sensing (C&S).Although the millimeter wave (mmWave) communication and mmWave radar sharesimilar multiple-input multiple-output (MIMO) architecture for integration, thefull potential of dual-function synergy remains to be exploited. In this paper,we commence by overviewing state-of-the-art schemes from the aspects ofwaveform design and signal processing. Nevertheless, these approaches face thedilemma of mutual compromise between C&S performance. To this end, we revealand exploit the synergy between C&S. In the proposed framework, we introduce atwo-stage frame structure and resort artificial intelligence (AI) to achievethe synergistic gain by designing a joint C&S channel semantic extraction andreconstruction network (JCASCasterNet). With just a cost-effective andenergy-efficient single sensing antenna, the proposed scheme achieves enhancedoverall performance while requiring only limited pilot and feedback signalingoverhead. In the end, we outline the challenges that lie ahead in the futuredevelopment of integrated sensing and communication networks, along withpromising directions for further research.

AI Empowered Channel Semantic Acquisition for 6G Integrated Sensing and Communication Networks