Trustworthy AI-Driven Dynamic Hybrid RIS: Joint Optimization and Reward Poisoning-Resilient Control in Cognitive MISO Networks
arXiv 2604.01238•2fd6859e6d0d4377f7b3cbe7b62a7213baae50559419e48849abc97b22ec2837
3.4 GHz channel measurementsDRL for resource management (CIVIC)ML for telecomO-RANPareto frontQ2NSQAOAQNOSSDQNUAV A2A channeladversarial ML defensescognitive radio networks (CRN)deep reinforcement learning (DRL)hybrid classical-quantummetaverse resource allocationmulti-objective MDPsns-3physics-informed transformerquantum networkingquantum simulatorquantum walksreconfigurable intelligent surface (RIS)reward poisoningsoft actor-critic (SAC)wideband CFR reconstruction
Paper metadata
- arXiv ID
- 2604.01238
- Version
- Not specified by this published record
- Category
- Computer Science — Networking and Internet Architecture (cs.NI)
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Evidence and limitations
- Source ID
- arxiv_cs_ni
- Record identifier
- 2fd6859e6d0d4377f7b3cbe7b62a7213baae50559419e48849abc97b22ec2837
- Enrichment time
- 2026-04-03T07:24:01Z
- AI-assisted enrichment
- Yes
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