21 citations · 32 across the 10 of their papers we have counts for
4 papers · 1 filter
FedCritic-MIMO: Communication-Efficient Serverless Federated Critic Learning for Massive-MIMO Resource Control in Open and Disaggregated 6G RANs
Amin Farajzadeh, Melike Erol-Kantarci
This paper proposes FedCritic-MIMO, a communication-efficient serverless federated multi-agent reinforcement learning framework for AI-native resource control across independently…
FedCritic: Serverless Federated Critic Learning-based Resource Allocation for Multi-Cell OFDMA in 6G
Amin Farajzadeh, Melike Erol-Kantarci
In sixth-generation (6G) ultra-dense networks, aggressive frequency reuse amplifies inter-cell interference (ICI), making multi-cell orthogonal frequency-division multiple access (…
Data-Driven Spectrum Demand Prediction: A Spatio-Temporal Framework with Transfer Learning
Amin Farajzadeh, Hongzhao Zheng, Sarah Dumoulin +3
Accurate spectrum demand prediction is crucial for informed spectrum allocation, effective regulatory planning, and fostering sustainable growth in modern wireless communication ne…
Federated Learning in NTNs: Design, Architecture and Challenges
Amin Farajzadeh, Animesh Yadav, Halim Yanikomeroglu
Non-terrestrial networks (NTNs) are emerging as a core component of future 6G communication systems, providing global connectivity and supporting data-intensive applications. In th…