Abstract
There emerges a strong trend recently to create an intelligent and controllable wireless transmission environment by installing reconfigurable intelligent surfaces (RIS) on the surface of diverse. We research the use of RIS in 5G multicast TV applications in this paper. In particular, the shape-adaptive RIS is developed to relay 5G multicast TV signals and achieve extra RIS gain. To optimize the shape bending in RIS model, we employ the algorithm of Deep Deterministic Policy Gradient (DDPG), a reinforcement learning technique that combines both Q-learning and Policy gradients. Our simulation results show that RIS can considerably enhance the SINR of worst users and improve the system’s overall Modulation and Coding Scheme (MCS) level for 5G mobile broadcasting services.
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