Adaptive Obstacle-Aware RIS Switch for Mobile mmWave Access Networks

Thanks to its capability of manipulating electromagnetic signals, the reconfigurable intelligent surface (RIS) is gaining momentum in alleviating the impact of blockages on mmWave signals, by providing redirected transmission paths. However, obstacles can also inevitably appear in the redirected paths. This can be solved by installing multiple RISs and switching among them. In this letter, for the first time, we adaptively switch among RISs for a mobile user in real time to optimize its achievable rate, without need for a priori knowledge on potential obstacles. We present an actor-critic based approach to learn unknown obstacles and variational spatial correlations originated by the user mobility, which is followed by the analysis on ergodic achievable rate. Experimental results have shown that the approach can achieve rates about 15% less than the optimum and 76% more than the state-of-the-art.