Estimating Channels by Transmitting Pilots from Reconfigurable Intelligent Surface

The rising reconfigurable intelligent surface (RIS) is a promising technology and a multitude of literature focuses on its channel estimation (CE), which is a critical and challenging task. Most existing works adopt a type of “cascaded channel” training scheme, where the “two-hop” channel cascaded by RIS is treated as one and measured by one shot. As unveiled by the latest researches, however, the concatenated channel suffers from severe fading loss and hence seriously degrades the CE precision. To resolve this difficulty, this paper proposes a novel training scheme. Specifically, being equipped with one transmit RF chain, the RIS broadcasts pilot signals to all other devices during the training period. This novel scheme can overcome double fading loss at a low hardware cost. The pilot design of the newly proposed training scheme is a difficult quartic optimization problem and we develop a gradient descent (GD) based solution to resolve it. Numerical results verify the effectiveness of our solution and demonstrate our training scheme can significantly outperform the traditional cascaded channel training method.