Daniel Ayepah-Mensah

Orcid: 0000-0001-9159-0509

According to our database1, Daniel Ayepah-Mensah authored at least 26 papers between 2018 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2025
AI-Native Collaborative Content Sharing in Blockchain-Empowered UAV-Assisted D2D Networks.
IEEE Internet Things J., August, 2025

FedCruise: Collaborative Cruise Guidance With Federated Policy Distillation in Multiple Ride-Hailing Platforms.
IEEE Internet Things J., April, 2025

Federated Policy Distillation for Digital Twin-Enabled Intelligent Resource Trading in 5G Network Slicing.
IEEE Trans. Netw. Serv. Manag., February, 2025

FeDistSlice: Federated Policy Distillation for Collaborative Intelligence in Multi-Tenant RAN Slicing.
IEEE Trans. Serv. Comput., 2025

Multiagent DRL-Based Consensus Mechanism for Blockchain-Based Collaborative Computing in UAV-Assisted 6G Networks.
IEEE Internet Things J., 2025

2024
Dynamic Pricing for Vehicle Dispatching in Mobility-as-a-Service Market via Multi-Agent Deep Reinforcement Learning.
IEEE Trans. Veh. Technol., August, 2024

Competitive Pricing for Resource Trading in Sliced Mobile Networks: A Multi-Agent Reinforcement Learning Approach.
IEEE Trans. Mob. Comput., May, 2024

Blockchain-Enabled Federated Learning-Based Resource Allocation and Trading for Network Slicing in 5G.
IEEE/ACM Trans. Netw., February, 2024

Adaptive Digital Twin and Communication-Efficient Federated Learning Network Slicing for 5G-enabled Internet of Things.
CoRR, 2024

2023
Holistic Roadmap of Trends in Radio Access Network Slicing: A Survey.
IEEE Commun. Mag., December, 2023

Consortium Blockchain-Based Spectrum Trading for Network Slicing in 5G RAN: A Multi-Agent Deep Reinforcement Learning Approach.
IEEE Trans. Mob. Comput., October, 2023

Stackelberg game-based dynamic resource trading for network slicing in 5G networks.
J. Netw. Comput. Appl., May, 2023

Two-Tier Resource Allocation for Multitenant Network Slicing: A Federated Deep Reinforcement Learning Approach.
IEEE Internet Things J., 2023

2022
Blockchain-Enabled Resource Trading and Deep Reinforcement Learning-Based Autonomous RAN Slicing in 5G.
IEEE Trans. Netw. Serv. Manag., 2022

Transfer Learning for Autonomous Cell Activation Based on Relational Reinforcement Learning With Adaptive Reward.
IEEE Syst. J., 2022

Deep Reinforcement Learning-Based Mobility-Aware UAV Content Caching and Placement in Mobile Edge Networks.
IEEE Syst. J., 2022

2020
Autonomous Resource Slicing for Virtualized Vehicular Networks With D2D Communications Based on Deep Reinforcement Learning.
IEEE Syst. J., 2020

Autonomous cell activation for energy saving in cloud-RANs based on dueling deep Q-network.
Knowl. Based Syst., 2020

End-to-end CNN-based dueling deep Q-Network for autonomous cell activation in Cloud-RANs.
J. Netw. Comput. Appl., 2020

Revised reinforcement learning based on anchor graph hashing for autonomous cell activation in cloud-RANs.
Future Gener. Comput. Syst., 2020

2019
Autonomous Resource Provisioning and Resource Customization for Mixed Traffics in Virtualized Radio Access Network.
IEEE Syst. J., 2019

Delay-aware content distribution via cell clustering and content placement for multiple tenants.
J. Netw. Comput. Appl., 2019

Dynamic Reservation and Deep Reinforcement Learning Based Autonomous Resource Slicing for Virtualized Radio Access Networks.
IEEE Access, 2019

Relational Reinforcement Learning Based Autonomous Cell Activation in Cloud-RANs.
IEEE Access, 2019

2018
Cell Virtualization with Network Partition for Initial User Association in Software Defined Small-cell Networks.
KSII Trans. Internet Inf. Syst., 2018

Low-complexity Dynamic Resource Slicing for Mixed Traffics in Virtualized Radio Access Network.
Proceedings of the 43rd IEEE Conference on Local Computer Networks, 2018


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