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Accelerating Energy-Efficient Federated Learning in Cell-Free Networks with Adaptive Quantization
Afsaneh Mahmoudi, Ming Xiao, Emil Björnson
Federated Learning (FL) enables clients to share learning parameters instead of local data, reducing communication overhead. Traditional wireless networks face latency challenges w…
Adaptive Quantization Resolution and Power Control for Federated Learning over Cell-free Networks
Afsaneh Mahmoudi, Emil Björnson
Federated learning (FL) is a distributed learning framework where users train a global model by exchanging local model updates with a server instead of raw datasets, preserving dat…
Joint Energy and Latency Optimization in Federated Learning over Cell-Free Massive MIMO Networks
Afsaneh Mahmoudi, Mahmoud Zaher, Emil Björnson
Federated learning (FL) is a distributed learning paradigm wherein users exchange FL models with a server instead of raw datasets, thereby preserving data privacy and reducing comm…