AI models for green communications towards 6G
Green communications have always been a target for the information industry to alleviate
energy overhead and reduce fossil fuel usage. In the current 5G and future 6G eras, there is …
energy overhead and reduce fossil fuel usage. In the current 5G and future 6G eras, there is …
Deep reinforcement learning in production systems: a systematic literature review
Shortening product development cycles and fully customisable products pose major
challenges for production systems. These not only have to cope with an increased product …
challenges for production systems. These not only have to cope with an increased product …
Deep reinforcement learning-based intelligent reflecting surface for secure wireless communications
In this paper, we study an intelligent reflecting surface (IRS)-aided wireless secure
communication system, where an IRS is deployed to adjust its reflecting elements to secure …
communication system, where an IRS is deployed to adjust its reflecting elements to secure …
Convergence of blockchain and edge computing for secure and scalable IIoT critical infrastructures in industry 4.0
Critical infrastructure systems are vital to underpin the functioning of a society and economy.
Due to the ever-increasing number of Internet-connected Internet-of-Things (IoT)/Industrial …
Due to the ever-increasing number of Internet-connected Internet-of-Things (IoT)/Industrial …
Deep learning in the industrial internet of things: Potentials, challenges, and emerging applications
Recent advances in the Internet of Things (IoT) are giving rise to a proliferation of
interconnected devices, allowing the use of various smart applications. The enormous …
interconnected devices, allowing the use of various smart applications. The enormous …
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 …
Intelligent resource slicing for eMBB and URLLC coexistence in 5G and beyond: A deep reinforcement learning based approach
In this paper, we study the resource slicing problem in a dynamic multiplexing scenario of
two distinct 5G services, namely Ultra-Reliable Low Latency Communications (URLLC) and …
two distinct 5G services, namely Ultra-Reliable Low Latency Communications (URLLC) and …
Artificial intelligence-based sensors for next generation IoT applications: A review
SC Mukhopadhyay, SKS Tyagi… - IEEE Sensors …, 2021 - ieeexplore.ieee.org
Sensors play a vital role in our daily lives and are an essential component for Internet of
Things (IoT) based systems as they enable the IoT to collect data to take smart and …
Things (IoT) based systems as they enable the IoT to collect data to take smart and …
Deep learning for the industrial internet of things (iiot): A comprehensive survey of techniques, implementation frameworks, potential applications, and future directions
The Industrial Internet of Things (IIoT) refers to the use of smart sensors, actuators, fast
communication protocols, and efficient cybersecurity mechanisms to improve industrial …
communication protocols, and efficient cybersecurity mechanisms to improve industrial …
Intelligent reflecting surface assisted anti-jamming communications: A fast reinforcement learning approach
Malicious jamming launched by smart jammers can attack legitimate transmissions, which
has been regarded as one of the critical security challenges in wireless communications …
has been regarded as one of the critical security challenges in wireless communications …