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Radio Resource Allocation in Cellular V2X: From Rule Based to Reinforcement Learning Based Approaches

Hegde, Anupama Ramesh (2024) Radio Resource Allocation in Cellular V2X: From Rule Based to Reinforcement Learning Based Approaches. Dissertation, Friedrich-Alexander-Universität Erlangen Nürnberg. doi: 10.25593/open-fau-899.

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Official URL: https://open.fau.de/handle/openfau/31444


Item URL in elib:https://elib.dlr.de/205631/
Document Type:Thesis (Dissertation)
Title:Radio Resource Allocation in Cellular V2X: From Rule Based to Reinforcement Learning Based Approaches
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Hegde, Anupama Rameshanupama.hegde (at) dlr.deUNSPECIFIEDUNSPECIFIED
Date:2024
Journal or Publication Title:Radio Resource Allocation in Cellular V2X: From Rule Based to Reinforcement Learning Based Approaches
Open Access:Yes
DOI:10.25593/open-fau-899
Number of Pages:186
Status:Published
Keywords:Cellular V2X Communication, Radio resource allocation, Sensing Based Semi Persistent Scheduling (SB-SPS), Multi-Agent Actor
Institution:Friedrich-Alexander-Universität Erlangen Nürnberg
Department:Chair of Computer Networks and Communication Systems
HGF - Research field:other
HGF - Program:other
HGF - Program Themes:other
DLR - Research area:no assignment
DLR - Program:no assignment
DLR - Research theme (Project):no assignment
Location: Oberpfaffenhofen
Institutes and Institutions:Institute of Communication and Navigation > Satellite Networks
Deposited By: Hegde, Anupama Ramesh
Deposited On:19 Aug 2024 14:32
Last Modified:19 Aug 2024 14:32

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