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Found 5 papers, 1 papers with code
Joint Energy and Latency Optimization in Federated Learning over Cell-Free Massive MIMO Networks
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 communication overhead.
Unknown Interference Modeling for Rate Adaptation in Cell-Free Massive MIMO Networks
Co-channel interference poses a challenge in any wireless communication network where the time-frequency resources are reused over different geographical areas.
A Bayesian Approach to Characterize Unknown Interference Power in Wireless Networks
The existence of unknown interference is a prevalent problem in wireless communication networks.
Soft Handover Procedures in mmWave Cell-Free Massive MIMO Networks
The algorithms provide a systematic procedure for initial access and update of the serving APs and assigned pilot sequence to each UE.
Learning-Based Downlink Power Allocation in Cell-Free Massive MIMO Systems
Further, we develop a clustered DNN model where the LSF parameters of a small number of APs, forming a cluster within a relatively large network, are used to jointly approximate the power coefficients of the cluster.
