  In this work, we examine the potential of autonomous operation of a
reconfigurable intelligent surface (RIS) using wireless energy harvesting from
information signals. To this end, we first identify the main RIS
power-consuming components and introduce a suitable power-consumption model.
Subsequently, we introduce a novel RIS power-splitting architecture that
enables simultaneous energy harvesting and beamsteering. Specifically, a subset
of the RIS unit cells (UCs) is used for beamsteering while the remaining ones
absorb energy. For the subset allocation, we propose policies obtained as
solutions to two optimization problems. The first problem aims at maximizing
the signal-to-noise ratio (SNR) at the receiver without violating the RIS's
energy harvesting demands. Additionally, the objective of the second problem is
to maximize the RIS harvested power, while ensuring an acceptable SNR at the
receiver. We prove that under particular propagation conditions, some of the
proposed policies deliver the optimal solution of the two problems.
Furthermore, we report numerical results that reveal the efficiency of the
policies with respect to the optimal and very high-complexity brute-force
design approach. Finally, through a case study of user tracking, we showcase
that the RIS power-consumption demands can be secured by harvesting energy from
information signals.
