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Found 6 papers, 0 papers with code
Rethinking Clustered Federated Learning in NOMA Enhanced Wireless Networks
This study explores the benefits of integrating the novel clustered federated learning (CFL) approach with non-orthogonal multiple access (NOMA) under non-independent and identically distributed (non-IID) datasets, where multiple devices participate in the aggregation with time limitations and a finite number of sub-channels.
A Community Detection and Graph Neural Network Based Link Prediction Approach for Scientific Literature
This study presents a novel approach that synergizes community detection algorithms with various Graph Neural Network (GNN) models to bolster link prediction in scientific literature networks.
Age of Information in Federated Learning over Wireless Networks
In this paper, federated learning (FL) over wireless networks is investigated.
Secrecy Sum Rate Maximization for a MIMO-NOMA Uplink Transmission in 6G networks
Non-orthogonal multiple access (NOMA), as a well-qualified candidate for sixth-generation (6G) mobile networks, has been attracting remarkable research interests due to high spectral efficiency and massive connectivity.
The Role of Urban Form in the Performance of Shared Automated Vehicles
The technology of Shared Automated Vehicles (SAVs) has advanced significantly in recent years.
Computers and Society J.4; J.6
Energy-Efficient Resource Allocation for NOMA enabled MEC Networks with Imperfect CSI
In this paper, we mainly focus on energy-efficient resource allocation for a multi-user, multi-BS NOMA assisted MEC network with imperfect channel state information (CSI), in which each user can upload its tasks to multiple base stations (BSs) for remote executions.
