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Federated Learning for 6G: Applications, Challenges, and Opportunities
Traditional machine learning is centralized in the cloud (data centers)....
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Optimal Resource Allocation for Multi-UAV Assisted Visible Light Communication
In this paper, the optimization of deploying unmanned aerial vehicles (U...
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Distributed Multi-agent Meta Learning for Trajectory Design in Wireless Drone Networks
In this paper, the problem of the trajectory design for a group of energ...
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Joint Location and Power Optimization for THz-enabled UAV Communications
In this paper, the problem of unmanned aerial vehicle (UAV) deployment a...
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A Machine Learning Approach for Task and Resource Allocation in Mobile Edge Computing Based Networks
In this paper, a joint task, spectrum, and transmit power allocation pro...
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Delay Minimization for Federated Learning Over Wireless Communication Networks
In this paper, the problem of delay minimization for federated learning ...
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UVeQFed: Universal Vector Quantization for Federated Learning
Traditional deep learning models are trained at a centralized server usi...
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Wireless Communications for Collaborative Federated Learning in the Internet of Things
Internet of Things (IoT) services will use machine learning tools to eff...
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Meta-Reinforcement Learning for Trajectory Design in Wireless UAV Networks
In this paper, the design of an optimal trajectory for an energy-constra...
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Energy-Efficient Wireless Communications with Distributed Reconfigurable Intelligent Surfaces
This paper investigates the problem of resource allocation for a wireles...
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Federated Learning for Task and Resource Allocation in Wireless High Altitude Balloon Networks
In this paper, the problem of minimizing energy and time consumption for...
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Machine Learning for Predictive Deployment of UAVs with Multiple Access
In this paper, a machine learning based deployment framework of unmanned...
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Federated Learning in the Sky: Joint Power Allocation and Scheduling with UAV Swarms
Unmanned aerial vehicle (UAV) swarms must exploit machine learning (ML) ...
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Artificial Intelligence Aided Next-Generation Networks Relying on UAVs
Artificial intelligence (AI) assisted unmanned aerial vehicle (UAV) aide...
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Convergence Time Optimization for Federated Learning over Wireless Networks
In this paper, the convergence time of federated learning (FL), when dep...
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Energy Efficient Federated Learning Over Wireless Communication Networks
In this paper, the problem of energy efficient transmission and computat...
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A Joint Learning and Communications Framework for Federated Learning over Wireless Networks
In this paper, the problem of training federated learning (FL) algorithm...
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Gated Recurrent Units Learning for Optimal Deployment of Visible Light Communications Enabled UAVs
In this paper, the problem of optimizing the deployment of unmanned aeri...
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Joint Access and Backhaul Resource Management in Satellite-Drone Networks: A Competitive Market Approach
In this paper, the problem of user association and resource allocation i...
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Analysis of Memory Capacity for Deep Echo State Networks
In this paper, the echo state network (ESN) memory capacity, which repre...
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Sum-Rate Maximization of Uplink Rate Splitting Multiple Access (RSMA) Communication
In this paper, the problem of maximizing the wireless users' sum-rate fo...
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Power Efficient Visible Light Communication (VLC) with Unmanned Aerial Vehicles (UAVs)
A novel approach that combines visible light communication (VLC) with un...
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A Vision of 6G Wireless Systems: Applications, Trends, Technologies, and Open Research Problems
The ongoing deployment of 5G cellular systems is continuously exposing t...
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Optimized Trajectory Design in UAV Based Cellular Networks for 3D Users: A Double Q-Learning Approach
In this paper, the problem of trajectory design of unmanned aerial vehic...
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Data Correlation-Aware Resource Management in Wireless Virtual Reality (VR): An Echo State Transfer Learning Approach
In this paper, the problem of wireless virtual reality (VR) resource man...
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Federated Echo State Learning for Minimizing Breaks in Presence in Wireless Virtual Reality Networks
In this paper, the problem of enhancing the virtual reality (VR) experie...
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Artificial Intelligence for Wireless Connectivity and Security of Cellular-Connected UAVs
Cellular-connected unmanned aerial vehicles (UAVs) will inevitably be in...
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Echo-Liquid State Deep Learning for 360^∘ Content Transmission and Caching in Wireless VR Networks with Cellular-Connected UAVs
In this paper, the problem of content caching and transmission is studie...
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Liquid State Machine Learning for Resource and Cache Management in LTE-U Unmanned Aerial Vehicle (UAV) Networks
In this paper, the problem of joint caching and resource allocation is i...
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Echo State Transfer Learning for Data Correlation Aware Resource Allocation in Wireless Virtual Reality
In this paper, the problem of data correlation-aware resource management...
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Machine Learning for Wireless Networks with Artificial Intelligence: A Tutorial on Neural Networks
Next-generation wireless networks must support ultra-reliable, low-laten...
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