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Mohammad Parvini
Mohammad Parvini
Communications Systems Researcher, TU Dresden
Verified email at tu-dresden.de - Homepage
Title
Cited by
Cited by
Year
AoI-aware resource allocation for platoon-based C-V2X networks via multi-agent multi-task reinforcement learning
M Parvini, MR Javan, N Mokari, B Abbasi, EA Jorswieck
IEEE Transactions on Vehicular Technology, 2023
292023
Spectrum sharing schemes from 4G to 5G and beyond: Protocol flow, regulation, ecosystem, economic
M Parvini, AH Zarif, A Nouruzi, N Mokari, MR Javan, B Abbasi, A Ghasemi, ...
IEEE Open Journal of the Communications Society 4, 464-517, 2023
172023
A comprehensive survey of spectrum sharing schemes from a standardization and implementation perspective
M Parvini, AH Zarif, A Nouruzi, N Mokari, MR Javan, B Abbasi, A Ghasemi, ...
arXiv preprint arXiv:2203.11125, 2022
92022
Berlin V2X: A machine learning dataset from multiple vehicles and radio access technologies
R Hernangómez, P Geuer, A Palaios, D Schäufele, C Watermann, ...
2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring), 1-5, 2023
82023
AoI aware radio resource management of autonomous platoons via multi agent reinforcement learning
M Parvini, MR Javan, N Mokari, BA Arand, EA Jorswieck
2021 17th International Symposium on Wireless Communication Systems (ISWCS), 1-6, 2021
72021
A secure and resilient 6G architecture vision of the German flagship project 6G-ANNA
M Hoffmann, G Kunzmann, T Dudda, R Irmer, A Jukan, G Macher, ...
IEEE Access, 2023
52023
Joint Resource Allocation and String-Stable CACC Design with Multi-Agent Reinforcement Learning
M Parvini, A González, A Villamil, P Schulz, G Fettweis
ICC 2023 - IEEE International Conference on Communications, 1232-1237, 2023
32023
A unified framework for joint energy and AoI optimization via deep reinforcement learning for NOMA MEC-based networks
A Zakeri, M Parvini, MR Javan, N Mokari, EA Jorswieck
arXiv preprint arXiv:2011.00436, 2020
32020
Toward an AI-Enabled Connected Industry: AGV Communication and Sensor Measurement Datasets
R Hernangómez, A Palaios, C Watermann, D Schäufele, P Geuer, ...
IEEE Communications Magazine 62 (4), 90-95, 2024
22024
A Low-Complexity Machine Learning Design for mmWave Beam Prediction
MQ Khan, A Gaber, M Parvini, P Schulz, G Fettweis
IEEE Wireless Communications Letters, 2024
12024
Resource Allocation in V2X Networks: From Classical Optimization to Machine Learning-Based Solutions
M Parvini, P Schulz, G Fettweis
IEEE Open Journal of the Communications Society, 2024
2024
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