Feature-oriented channel estimation in reconfigurable intelligent surface-assisted wireless communication systems

In this6study, the channel estimation problem is investigated for a wireless communication system assisted by a reconfigurable intelligent surface (RIS). The RIS thus creates an assistant channel, which has the features of positivity and dominance. Owing to these features, the channel estimation problem is formulated as a constrained residual sum of squares minimisation problem, which differs radically from the traditional channel estimation issue. An efficient Lagrange multiplier and dual ascent-based estimation scheme is then designed to obtain an iterative solution for the estimator. Moreover, the Cramér-Rao lower bounds are deduced as a performance benchmark. Simulation results show that the authors' designed scheme improves the estimation accuracy up to 33%, compared with the conventional least-square method in the low signal-to-noise ratio regime.