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D4.2 Modelling of Intelligent IAB and Hybrid User Terminal Optimized by the Multi-agent Deep Reinforcement Learning

Authors :
Koffman, Israel
Globen, Baruch
Eappen, Geoffrey
Cosmas, John
Nilavalan, Raj
Xia, Guoqing
Li, Bohan
Zhou, Huiyu
Hou, Jiancao
Gavras, Anastasius
Kazmierowski, Alexandre
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

Details

Language :
English
Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....d06fc1809f766d6493bfc0c0378a5ab0
Full Text :
https://doi.org/10.5281/zenodo.7467961