A Three-Party Repeated Coalition Formation Game for PLS in Wireless Communications with IRSs
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arXiv
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| Format: | Preprint |
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2024
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| author | Zhou, Haipeng Chen, Ruoyang Yi, Changyan Li, Juan Cai, Jun |
| author_facet | Zhou, Haipeng Chen, Ruoyang Yi, Changyan Li, Juan Cai, Jun |
| contents | In this paper, a repeated coalition formation game (RCFG) with dynamic decision-making for physical layer security (PLS) in wireless communications with intelligent reflecting surfaces (IRSs) has been investigated. In the considered system, one central legitimate transmitter (LT) aims to transmit secret signals to a group of legitimate receivers (LRs) under the threat of a proactive eavesdropper (EV), while there exist a number of third-party IRSs (TIRSs) which can choose to form a coalition with either legitimate pairs (LPs) or the EV to improve their respective performances in exchange for potential benefits (e.g., payments). Unlike existing works that commonly restricted to friendly IRSs or malicious IRSs only, we study the complicated dynamic ally-adversary relationships among LPs, EV and TIRSs, under unpredictable wireless channel conditions, and introduce a RCFG to model their long-term strategic interactions. Particularly, we first analyze the existence of Nash equilibrium (NE) in the formulated RCFG, and then propose a switch operations-based coalition selection along with a deep reinforcement learning (DRL)-based algorithm for obtaining such equilibrium. Simulations examine the feasibility of the proposed algorithm and show its superiority over counterparts. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_11500 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Three-Party Repeated Coalition Formation Game for PLS in Wireless Communications with IRSs Zhou, Haipeng Chen, Ruoyang Yi, Changyan Li, Juan Cai, Jun Computer Science and Game Theory Networking and Internet Architecture In this paper, a repeated coalition formation game (RCFG) with dynamic decision-making for physical layer security (PLS) in wireless communications with intelligent reflecting surfaces (IRSs) has been investigated. In the considered system, one central legitimate transmitter (LT) aims to transmit secret signals to a group of legitimate receivers (LRs) under the threat of a proactive eavesdropper (EV), while there exist a number of third-party IRSs (TIRSs) which can choose to form a coalition with either legitimate pairs (LPs) or the EV to improve their respective performances in exchange for potential benefits (e.g., payments). Unlike existing works that commonly restricted to friendly IRSs or malicious IRSs only, we study the complicated dynamic ally-adversary relationships among LPs, EV and TIRSs, under unpredictable wireless channel conditions, and introduce a RCFG to model their long-term strategic interactions. Particularly, we first analyze the existence of Nash equilibrium (NE) in the formulated RCFG, and then propose a switch operations-based coalition selection along with a deep reinforcement learning (DRL)-based algorithm for obtaining such equilibrium. Simulations examine the feasibility of the proposed algorithm and show its superiority over counterparts. |
| title | A Three-Party Repeated Coalition Formation Game for PLS in Wireless Communications with IRSs |
| topic | Computer Science and Game Theory Networking and Internet Architecture |
| url | https://arxiv.org/abs/2402.11500 |