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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 on-demand to individual operators to support their transmissions. When an operator takes control of a RIS, it can adjust its phase-response 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.
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Štefan Schwarz (2024) studied this question.
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