Machine learning-assisted adaptive modulation for optimized drone-user communication in b5g
SP Gopi, M Magarini, SH Alsamhi, AV Shvetsov - Drones, 2021 - mdpi.com
The fundamental issue for Beyond fifth Generation (B5G) is providing a pervasive
connection to heterogeneous and various devices in smart environments. Therefore, Drones …
connection to heterogeneous and various devices in smart environments. Therefore, Drones …
LoRaWAN Meets ML: A Survey on Enhancing Performance with Machine Learning
The Internet of Things is rapidly growing with the demand for low-power, long-range
wireless communication technologies. Long Range Wide Area Network (LoRaWAN) is one …
wireless communication technologies. Long Range Wide Area Network (LoRaWAN) is one …
Federated learning-based cell-free massive MIMO system for privacy-preserving
Cell-free massive MIMO (CF mMIMO) is a promising next generation wireless architecture to
realize federated learning (FL). However, sensitive information of user equipments (UEs) …
realize federated learning (FL). However, sensitive information of user equipments (UEs) …
Double deep q-network method for energy efficiency and throughput in a uav-assisted terrestrial network
Increasing the coverage and capacity of cellular networks by deploying additional base
stations is one of the fundamental objectives of fifth-generation (5G) networks. However, it …
stations is one of the fundamental objectives of fifth-generation (5G) networks. However, it …
Hcfl: A high compression approach for communication-efficient federated learning in very large scale iot networks
Federated learning (FL) is a new artificial intelligence concept that enables Internet-of-
Things (IoT) devices to learn a collaborative model without sending the raw data to …
Things (IoT) devices to learn a collaborative model without sending the raw data to …
Deep learning enhanced NOMA system: A survey on future scope and challenges
V Andiappan, V Ponnusamy - Wireless Personal Communications, 2022 - Springer
As a key important approach for next generation communication systems, Non-Orthogonal
Multiple Access (NOMA) has made high attention in the wireless communication. NOMA …
Multiple Access (NOMA) has made high attention in the wireless communication. NOMA …
Prediction of COVID-19 risk in public areas using IoT and machine learning
COVID-19 is a community-acquired infection with symptoms that resemble those of influenza
and bacterial pneumonia. Creating an infection control policy involving isolation, disinfection …
and bacterial pneumonia. Creating an infection control policy involving isolation, disinfection …
AI-ERA: Artificial intelligence-empowered resource allocation for LoRa-enabled IoT applications
Adaptive data rate (ADR) is a widely adopted resource assignment approach in long-range
wide-area networks (LoRaWANs) for static Internet of Things (IoT) applications such as …
wide-area networks (LoRaWANs) for static Internet of Things (IoT) applications such as …
[HTML][HTML] Improve quality of service for the Internet of Things using blockchain & machine learning algorithms
LN CheSuh, RÁ Fernández-Diaz, JM Alija-Perez… - Internet of Things, 2024 - Elsevier
The quality of service (QoS) parameters in IoT applications plays a prominent role in
determining the performance of an application. Considering the significance and popularity …
determining the performance of an application. Considering the significance and popularity …
Hierarchical multi-agent DRL-based framework for joint multi-RAT assignment and dynamic resource allocation in next-generation hetnets
This article considers the problem of cost-aware downlink sum-rate maximization via joint
optimal radio access technologies (RATs) assignment and power allocation in next …
optimal radio access technologies (RATs) assignment and power allocation in next …