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D4.2 Modelling of Intelligent IAB and Hybrid User Terminal Optimized by the Multi-agent Deep Reinforcement Learning
- Publication Year :
- 2022
- Publisher :
- Zenodo, 2022.
-
Abstract
- This document updates the progress made in the different research areas related to 6G Access Architecture performed in the 6G BRAINS project. The updated research areas in this document include: Artificial Intelligence (AI) based scheduler for a 5G Cell-Free (CF) networks with Integrated Access and Back-haul (IAB) Grant-free NOMA for massive Machine-Type Communication Hybrid user terminal modelling for the D2D enabled cooperative network Intelligent IAB with Beam Steering based on User Location Advanced Test and Simulation Tools supporting 6G BRAINS research
- Subjects :
- IAB, Reinforcement Learning, Cell Free, Device to Device
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....d06fc1809f766d6493bfc0c0378a5ab0
- Full Text :
- https://doi.org/10.5281/zenodo.7467961