Multi-Agent DRL for QoS and Energy Optimization in RIS-Enabled Open-RAN Industrial 6G TN/NTN Networks
arXiv 2606.28339•aa4bd7cc6c1bf1a1e3cdd4c42bbbfdf47e942a38ae96186fad98e77cfc72b4c5
5G6GCornerCaseDec-POMDPETSI-VAMHTTPIPFSLLM-assisted-testingOpen-RANRISUAV-RISV2Xbandwidth-constraintsdecentralized-learningdifferential-testingedge-computingh2ointention-sharing','uncertainty-ellipses'latencymobilitymulti-agent-DRLprotocol-bugsprotocol-testingproximity-servicesstateless-ABR
Paper metadata
- arXiv ID
- 2606.28339
- 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
- aa4bd7cc6c1bf1a1e3cdd4c42bbbfdf47e942a38ae96186fad98e77cfc72b4c5
- Enrichment time
- 2026-06-30T07:23:49Z
- AI-assisted enrichment
- Yes
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