Federated learning for metaverse: A survey
The metaverse, which is at the stage of innovation and exploration, faces the dilemma of
data collection and the problem of private data leakage in the process of development. This …
data collection and the problem of private data leakage in the process of development. This …
Federated ensemble-learning for transport mode detection in vehicular edge network
Abstract Transport Mode Detection (TMD) has become a crucial part of Intelligent
Transportation Systems (ITS) thanks to the recent advancements in Artificial Intelligence and …
Transportation Systems (ITS) thanks to the recent advancements in Artificial Intelligence and …
Mobility-aware split-federated with transfer learning for vehicular semantic communication networks
Machine learning-based semantic communication is a promising enabler for future-
generation wireless network systems such as 6G networks. In practice, effective semantic …
generation wireless network systems such as 6G networks. In practice, effective semantic …
Age-of-information minimization in federated learning based networks with Non-IID dataset
In this paper, a federated learning (FL) based system is investigated with non-independent
and identically distributed (non-IID) dataset, where multiple devices participate in the global …
and identically distributed (non-IID) dataset, where multiple devices participate in the global …
Distributed intelligence in wireless networks
The cloud-based solutions are becoming inefficient due to considerably large time delays,
high power consumption, and security and privacy concerns caused by billions of connected …
high power consumption, and security and privacy concerns caused by billions of connected …
Federated learning in massive MIMO 6G networks: Convergence analysis and communication-efficient design
In federated learning (FL), model weights must be updated at local users and the base
station (BS). These weights are subjected to uplink (UL) and downlink (DL) transmission …
station (BS). These weights are subjected to uplink (UL) and downlink (DL) transmission …
Communication-efficient ADMM-based federated learning
Federated learning has shown its advances over the last few years but is facing many
challenges, such as how algorithms save communication resources, how they reduce …
challenges, such as how algorithms save communication resources, how they reduce …
Mobile reconfigurable intelligent surfaces for NOMA networks: Federated learning approaches
A novel framework of reconfigurable intelligent surfaces (RISs)-enhanced indoor wireless
networks is proposed, where an RIS mounted on the robot is invoked to enable mobility of …
networks is proposed, where an RIS mounted on the robot is invoked to enable mobility of …
Wirelessly powered federated learning networks: Joint power transfer, data sensing, model training, and resource allocation
Federated learning (FL) has found many successes in wireless communications; however,
the implementation of FL has been hindered by the energy limitation of mobile devices …
the implementation of FL has been hindered by the energy limitation of mobile devices …
Federated learning for physical layer design
AM Elbir, AK Papazafeiropoulos… - IEEE Communications …, 2021 - ieeexplore.ieee.org
Model-free techniques, such as machine learning (ML), have recently attracted much
interest toward the physical layer design (eg, symbol detection, channel estimation, and …
interest toward the physical layer design (eg, symbol detection, channel estimation, and …