Gambling on Reconfigurable Intelligent Surfaces

We consider multi-operator wireless networks where broadband reconfigurable intelligent surfaces (RISs) effectively cover the transmission bands of all operators.These RISs are supplied by a dedicated provider and dynamically leased ondemand to individual operators to support their transmissions.When an operator takes control of a RIS, it can adjust its phaseresponse to meet the requirements of its users.This sets the stage for a competitive scenario where operators vie for control of RISs.To address this competition, we introduce an auction format designed to efficiently allocate RISs to operators.Furthermore, we develop a multi-agent reinforcement learning environment to optimize operators' bidding strategies, demonstrating its superiority over the heuristic dominant strategy of greedy bidding.