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Found 6 papers, 1 papers with code
Multi-Agent Reinforcement Learning for Power Control in Wireless Networks via Adaptive Graphs
The ever-increasing demand for high-quality and heterogeneous wireless communication services has driven extensive research on dynamic optimization strategies in wireless networks.
A Distributed Neural Linear Thompson Sampling Framework to Achieve URLLC in Industrial IoT
Industrial Internet of Things (IIoT) networks will provide Ultra-Reliable Low-Latency Communication (URLLC) to support critical processes underlying the production chains.
Data-driven Predictive Latency for 5G: A Theoretical and Experimental Analysis Using Network Measurements
The advent of novel 5G services and applications with binding latency requirements and guaranteed Quality of Service (QoS) hastened the need to incorporate autonomous and proactive decision-making in network management procedures.
Uplink Scheduling in Federated Learning: an Importance-Aware Approach via Graph Representation Learning
Federated Learning (FL) has emerged as a promising framework for distributed training of AI-based services, applications, and network procedures in 6G.
Distributed Resource Allocation for URLLC in IIoT Scenarios: A Multi-Armed Bandit Approach
This paper addresses the problem of enabling inter-machine Ultra-Reliable Low-Latency Communication (URLLC) in future 6G Industrial Internet of Things (IIoT) networks.
Packet Speed and Cost in Mobile Wireless Delay-Tolerant Networks
A mobile wireless delay-tolerant network (DTN) model is proposed and analyzed, in which infinitely many nodes are initially placed on R^2 according to a uniform Poisson point process (PPP) and subsequently travel, independently of each other, along trajectories comprised of line segments, changing travel direction at time instances that form a Poisson process, each time selecting a new travel direction from an arbitrary distribution; all nodes maintain constant speed.
Information Theory Information Theory
