Max-Min Fairness in Intelligent Reflecting Surface-aided Multi-Operator Networks with Coop...

This study investigates a scenario where multiple mobile network operators (MNOs) share an intelligent reflecting surface (IRS), a technology that efficiently manipulates electromagnetic waves. Although IRSs are energy-efficient, constraints on their installation lead to competition among MNOs, increasing redundancy and energy consumption. In a multi-MNO environment, achieving fairness and optimizing performance is crucial. To address these challenges, this study proposes a cooperative passive beamforming strategy for maximizing the minimum achievable rate among users of different MNOs. An algorithm based on the projected gradient ascent (PGA) method is introduced to resolve the inherent complexity of this max-min fairness problem. Numerical evaluations demonstrate that the proposed IRS-sharing approach outperforms traditional single MNO-specific and sequential IRS control schemes. These findings highlight the potential benefits of IRS sharing, underscoring its practical value in enhancing network efficiency and fairness in multi-operator scenarios.

Max-Min Fairness in Intelligent Reflecting Surface-aided Multi-Operator Networks with Cooperative Passive Beamforming

Hiroaki Hashida, Yuichi Kawamoto, Nei Kato, Tohoku University