Game-theoretic robotic offloading via multi-agent learning for agricultural applications in heterogeneous networks

A Zhu, Z Zeng, S Guo, H Lu, M Ma, Z Zhou - Computers and Electronics in …, 2023 - Elsevier
Intelligent robotics, as a frontier field of widespread attention, is increasingly applied to
realize cyber-physical-social system (CPSS). Taking Agriculture 4.0 as one use case, using …

Coverage optimization for large-scale mobile networks with digital twin and multi-agent reinforcement learning

H Liu, T Li, F Jiang, W Su… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
With the exponential growth of mobile users, ensuring high-quality network coverage has
become paramount. Large-scale mobile networks consist of numerous base stations (BSs) …

On joint cooperative relaying, resource allocation, and scheduling for mobile edge computing networks

N Biswas, Z Wang, L Vandendorpe… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
In this paper, we consider Internet of Things (IoT) based mobile edge computing (MEC)
system. IoT devices are controlled by access points (APs), which do not have access to any …

AI-Driven Ground Robots: Mobile Edge Computing and mmWave Communications at Work

G Baruffa, A Detti, L Rugini, F Crocetti… - IEEE Open Journal …, 2024 - ieeexplore.ieee.org
The seamless integration of multiple radio access technologies (multi-RAT) and cloud/edge
resources is pivotal for advancing future networks, which seek to unify distributed and …

[HTML][HTML] Sea-Based UAV Network Resource Allocation Method Based on an Attention Mechanism

Z Mao, Z Zhang, F Lu, Y Pan, T Zhang, J Kang, Z Zhao… - Electronics, 2024 - mdpi.com
As humans continue to exploit the ocean, the number of UAV nodes at sea and the demand
for their services are increasing. Given the dynamic nature of marine environments …

An Intelligent Hybrid Radio Access Technology Selection Algorithm for 5G-Satellite Network

M Bello, P Pillai, A Sadiq - 2021 IEEE Mysore Sub Section …, 2021 - ieeexplore.ieee.org
Cellular networks are anticipated to handle a significant increase in data traffic, as well as a
huge number of devices and new use cases in the very near future; therefore, future 5G …

Machine learning approach of multi‐RAT selection for travelling users in 5G NSA networks

NO Salau, S Manzoor, MZ Shakir - IET Networks, 2023 - Wiley Online Library
The rapid increment of mobile device usage and the corresponding huge data volume
generated afterwards, necessitated the utilisation of the 5G network spectrum. This is …

DRL-Driven Intelligent Access Traffic Management for Hybrid 5G-WiFi Multi-RAT Networks

X Zhou, H Li, A Bravalheri, A Emami… - 2023 IEEE 34th …, 2023 - ieeexplore.ieee.org
Integrating mobile networks with Non-3GPP networks provides a promising solution to
mitigate the wireless RF spectrum scarcity. Despite the maturity of integration technologies …

Latency‐Based Routing for SDN‐OpenFlow Networks

HB Valiveti, K Meenakshi, K Swaraja… - Software Defined …, 2022 - Wiley Online Library
The increasing demand and the varied signaling mobile traffic patterns of 5G networks to
service huge volumes of data provides an exemplary infrastructure for trillions of new …

Power Saving in Multi-Hop Device to Device Communication

Z Aslam, A Gupta, D Deepak… - 2023 4th International …, 2023 - ieeexplore.ieee.org
In this paper a method has been proposed to save power in multi-hop Device to Device
communication. D2D [1] communication provides a lot of advantages like increase in …