Generative joint source-channel coding for semantic image transmission
Recent works have shown that joint source-channel coding (JSCC) schemes using deep
neural networks (DNNs), called DeepJSCC, provide promising results in wireless image …
neural networks (DNNs), called DeepJSCC, provide promising results in wireless image …
Multiagent reinforcement learning meets random access in massive cellular internet of things
Internet of Things (IoT) has attracted considerable attention in recent years due to its
potential of interconnecting a large number of heterogeneous wireless devices. However, it …
potential of interconnecting a large number of heterogeneous wireless devices. However, it …
Toward joint learning of optimal MAC signaling and wireless channel access
A Valcarce, J Hoydis - IEEE Transactions on Cognitive …, 2021 - ieeexplore.ieee.org
Communication protocols are the languages used by network nodes. Before a user
equipment (UE) exchanges data with a base station (BS), it must first negotiate the …
equipment (UE) exchanges data with a base station (BS), it must first negotiate the …
Semi-grant-free orthogonal multiple access with partial-information for short packet transmissions
Traditional multiple access schemes, as well as more recent preamble-based schemes,
cannot achieve the extremely low latency, complexity, and collision probability required by …
cannot achieve the extremely low latency, complexity, and collision probability required by …
Information-centric grant-free access for IoT fog networks: Edge vs. cloud detection and learning
A multi-cell Fog-Radio Access Network (F-RAN) architecture is considered in which Internet
of Things (IoT) devices periodically make noisy observations of a Quantity of Interest (QoI) …
of Things (IoT) devices periodically make noisy observations of a Quantity of Interest (QoI) …
Reinforcement learning random access for delay-constrained heterogeneous wireless networks: A two-user case
D Wu, L Deng, Z Liu, Y Zhang… - 2021 IEEE Globecom …, 2021 - ieeexplore.ieee.org
In this paper, we investigate the random access problem for a delay-constrained
heterogeneous wireless network. As a first attempt to study this new problem, we consider a …
heterogeneous wireless network. As a first attempt to study this new problem, we consider a …
Coordinated random access for industrial IoT with correlated traffic by reinforcement-learning
We propose a coordinated random access scheme for industrial Internet-of-things (IIoT)
scenarios, with machine-type devices (MTDs) generating sporadic correlated traffic. This …
scenarios, with machine-type devices (MTDs) generating sporadic correlated traffic. This …
[HTML][HTML] Cooperative Multi-Agent Reinforcement Learning for Data Gathering in Energy-Harvesting Wireless Sensor Networks
E Dvir, M Shifrin, O Gurewitz - Mathematics, 2024 - mdpi.com
This study introduces a novel approach to data gathering in energy-harvesting wireless
sensor networks (EH-WSNs) utilizing cooperative multi-agent reinforcement learning …
sensor networks (EH-WSNs) utilizing cooperative multi-agent reinforcement learning …
Connectionless transmission in wireless networks (IoT)
I Hmedoush - 2022 - theses.hal.science
The origin of the idea of adding intelligence to basic objects and making them communicate
has been lost to history. But in recent times, the emergence of the Internet as a global …
has been lost to history. But in recent times, the emergence of the Internet as a global …
Communication-Efficient Regret-Optimal Distributed Online Convex Optimization
Online convex optimization in distributed systems has shown great promise in
collaboratively learning on data streams with massive learners, such as in collaborative …
collaboratively learning on data streams with massive learners, such as in collaborative …