Integrated Sensing and Communication

Integrated sensing and communication (ISAC) aims to synergistically combine sensing and communication functionalities within a shared hardware platform, improving spectral and energy efficiency. Current research heavily focuses on addressing the challenges of dynamic environments (e.g., vehicular networks) and imperfect channel information, employing deep reinforcement learning, and various neural network architectures (e.g., CNNs, ELMs, transformers) for tasks like precoding, channel estimation, and user tracking. This integrated approach holds significant promise for enhancing the performance of next-generation wireless systems and enabling new applications in areas such as autonomous driving and industrial automation.