From federated to fog learning: Distributed machine learning over heterogeneous wireless networks
S Hosseinalipour, CG Brinton… - IEEE …, 2020 - ieeexplore.ieee.org
… in the design of distributed ML techniques. These heterogeneous communication characteristics
have motivated several recent studies on federated learning for wireless networks (eg, […
have motivated several recent studies on federated learning for wireless networks (eg, […
AI in 6G: Energy-efficient distributed machine learning for multilayer heterogeneous networks
MA Hossain, AR Hossain, N Ansari - IEEE Network, 2022 - ieeexplore.ieee.org
… intelligence (AI) and mobile networks will allow for the dynamic and automatic configuration
of network … We present our proposed heterogeneous network (HetNet) architecture …
of network … We present our proposed heterogeneous network (HetNet) architecture …
Distributed machine learning for wireless communication networks: Techniques, architectures, and applications
… DML architectures and their applications to wireless networks. The key features of different
… FEEL is leveraged in a heterogeneous cellular network in [118], in which micro-BSs or pico-…
… FEEL is leveraged in a heterogeneous cellular network in [118], in which micro-BSs or pico-…
Hybrid architectures for distributed machine learning in heterogeneous wireless networks
… CONCLUSION In this article, we propose two hybrid architectures for distributed ML in
heterogeneous wireless networks, namely, HSFL, and HFSL, based on integrating federated and …
heterogeneous wireless networks, namely, HSFL, and HFSL, based on integrating federated and …
Distributed learning in wireless networks: Recent progress and future challenges
… Abstract— The next-generation of wireless networks will enable many machine learning (ML) …
must jointly account for the network topology, device heterogeneity, wireless dynamics, FL …
must jointly account for the network topology, device heterogeneity, wireless dynamics, FL …
Parallel successive learning for dynamic distributed model training over heterogeneous wireless networks
… and model inertia in distributed machine learning. We then propose networkaware dynamic
… a novel methodology for distributing ML over wireless networks that leverages the following …
… a novel methodology for distributing ML over wireless networks that leverages the following …
Deep-reinforcement learning multiple access for heterogeneous wireless networks
… Heterogeneous Wireless Networks We consider time-slotted heterogeneous wireless networks
… packets to an access point (AP) via a shared wireless channel, as illustrated in Fig. 2. We …
… packets to an access point (AP) via a shared wireless channel, as illustrated in Fig. 2. We …
Multi-agent deep reinforcement learning multiple access for heterogeneous wireless networks with imperfect channels
… a common wireless spectrum and each network is unaware … distributed deep reinforcement
learning (DRL) based MAC protocol for a particular network, and the objective of this network …
learning (DRL) based MAC protocol for a particular network, and the objective of this network …
Deep learning based user association in heterogeneous wireless networks
Y Zhang, L Xiong, J Yu - IEEE Access, 2020 - ieeexplore.ieee.org
… In this paper, we study the user association problem from a deep learning perspective.
We propose a U-Net based deep learning scheme aimed at intelligently associating user …
We propose a U-Net based deep learning scheme aimed at intelligently associating user …
Distributed deep reinforcement learning-based spectrum and power allocation for heterogeneous networks
This paper investigates the problem of distributed resource management in two-tier
heterogeneous networks, where each cell selects its joint device association, spectrum allocation, …
heterogeneous networks, where each cell selects its joint device association, spectrum allocation, …
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