[HTML][HTML] Spectrum sensing, clustering algorithms, and energy-harvesting technology for cognitive-radio-based internet-of-things networks
X Fernando, G Lăzăroiu - Sensors, 2023 - mdpi.com
The aim of this systematic review was to identify the correlations between spectrum sensing,
clustering algorithms, and energy-harvesting technology for cognitive-radio-based internet …
clustering algorithms, and energy-harvesting technology for cognitive-radio-based internet …
The applicability of reinforcement learning methods in the development of industry 4.0 applications
Reinforcement learning (RL) methods can successfully solve complex optimization
problems. Our article gives a systematic overview of major types of RL methods, their …
problems. Our article gives a systematic overview of major types of RL methods, their …
A survey and future directions on clustering: From WSNs to IoT and modern networking paradigms
Many Internet of Things (IoT) networks are created as an overlay over traditional ad-hoc
networks such as Zigbee. Moreover, IoT networks can resemble ad-hoc networks over …
networks such as Zigbee. Moreover, IoT networks can resemble ad-hoc networks over …
Algorithm for Energy Resource Allocation and Sensor‐Based Clustering in M2M Communication Systems
Recent years have seen a surge in curiosity in machine‐to‐machine (M2M) collaborations
between academics and industry. Machine‐to‐machine communication devices (MTCDs) …
between academics and industry. Machine‐to‐machine communication devices (MTCDs) …
Buffer-aided relay selection for cooperative hybrid NOMA/OMA networks with asynchronous deep reinforcement learning
This paper investigates asynchronous reinforcement learning algorithms for joint buffer-
aided relay selection and power allocation in the non-orthogonal-multiple-access (NOMA) …
aided relay selection and power allocation in the non-orthogonal-multiple-access (NOMA) …
[HTML][HTML] An intelligent cluster-based routing scheme in 5G flying ad hoc networks
Flying ad hoc network (FANET) is an application of 5G access network, which consists of
unmanned aerial vehicles or flying nodes with scarce resources and high mobility rates. This …
unmanned aerial vehicles or flying nodes with scarce resources and high mobility rates. This …
Joint buffer-aided hybrid-duplex relay selection and power allocation for secure cognitive networks with double deep Q-network
This paper applies the reinforcement learning in the joint relay selection and power
allocation in the secure cognitive radio (CR) relay network, where the data buffers and full …
allocation in the secure cognitive radio (CR) relay network, where the data buffers and full …
Machine learning for disseminating cooperative awareness messages in cellular V2V communications
L Lusvarghi, ML Merani - IEEE Transactions on Vehicular …, 2022 - ieeexplore.ieee.org
This paper develops a novel Machine Learning (ML)-based strategy to distribute aperiodic
Cooperative Awareness Messages (CAMs) through cellular Vehicle-to-Vehicle (V2V) …
Cooperative Awareness Messages (CAMs) through cellular Vehicle-to-Vehicle (V2V) …
Energy Optimization‐Based Clustering Protocols in Wireless Sensor Networks and Internet of Things‐Survey
VKH Prasad, S Periyasamy - International Journal of …, 2023 - Wiley Online Library
Research on popular themes today is mainly concentrated on cutting‐edge home
applications made up of Internet of Things gadgets. As its principal means of sensing …
applications made up of Internet of Things gadgets. As its principal means of sensing …
A survey on LTE/LTE-A radio resource allocation techniques for machine-to-machine communication for B5G networks
Machine-to-Machine (M2M) communication refers to autonomous communication among
devices that aims for a massive number of connected devices. M2M communication can …
devices that aims for a massive number of connected devices. M2M communication can …