On the Achievable Rate Maximization in RIS Enhanced Ambient Backscatter Communication Systems

Ambient backscatter communication (AmBC) has emerged as a promising low-power communication technology. However, the achievable data rate of these systems is limited by the energy harvested at the tag. Existing works adopted reconfigurable intelligent surface (RIS) to increase either energy collection or achievable data rate. This letter proposes to improve both the forward link (from transmitter to tag) and backward link (from tag to receiver) in a RIS-assisted AmBC system. Such dual enhancement improves both the energy collection at the tag and the achievable rate at the receiver at the same time. We formulated an achievable rate maximization problem with the constraint of energy collection and then it was transformed into a convex form using Taylor approximation and quadratic transformation. Simulation results demonstrate that our proposed scheme outperforms several baselines in terms of both achievable data rate and energy collection failed percentage.