Unleashing the power of IoT: A comprehensive review of IoT applications and future prospects in healthcare, agriculture, smart homes, smart cities, and industry 4.0
The Internet of Things (IoT) technology and devices represent an exciting field in computer
science that is rapidly emerging worldwide. The demand for automation and efficiency has …
science that is rapidly emerging worldwide. The demand for automation and efficiency has …
Survey on joint paradigm of 5G and SDN emerging mobile technologies: Architecture, security, challenges and research directions
Modern communication systems are probable to surface new challenges while introducing
innovative fronts concerning context consciousness in wireless networks. The main outcome …
innovative fronts concerning context consciousness in wireless networks. The main outcome …
Dynamic task offloading for digital twin-empowered mobile edge computing via deep reinforcement learning
Limited by battery and computing resources, the computing-intensive tasks generated by
Internet of Things (IoT) devices cannot be processed all by themselves. Mobile edge …
Internet of Things (IoT) devices cannot be processed all by themselves. Mobile edge …
Meta-reinforcement learning based resource allocation for dynamic V2X communications
This paper studies the allocation of shared resources between vehicle-to-infrastructure (V2I)
and vehicle-to-vehicle (V2V) links in vehicle-to-everything (V2X) communications. In existing …
and vehicle-to-vehicle (V2V) links in vehicle-to-everything (V2X) communications. In existing …
Resource allocation for IRS assisted SGF NOMA transmission: A MADRL approach
J Chen, L Guo, J Jia, J Shang… - IEEE Journal on Selected …, 2022 - ieeexplore.ieee.org
Non-orthogonal multiple access (NOMA) assisted semi-grant-free (SGF) transmission has
been viewed as one of the promising technologies to meet massive connectivity …
been viewed as one of the promising technologies to meet massive connectivity …
Resource scheduling based on deep reinforcement learning in UAV assisted emergency communication networks
Unmanned aerial vehicle (UAV) assisted emergency communication is an important
technique for future B5G/6G scenario. The UAV is usually considered as a mobile relay to …
technique for future B5G/6G scenario. The UAV is usually considered as a mobile relay to …
Intelligent resource allocation for IRS-enhanced OFDM communication systems: A hybrid deep reinforcement learning approach
Orthogonal frequency division multiplexing (OFDM) systems have been widely applied in
practice since OFDM has diverse outstanding advantages. However, their performance …
practice since OFDM has diverse outstanding advantages. However, their performance …
Transmit power pool design for grant-free NOMA-IoT networks via deep reinforcement learning
Grant-free non-orthogonal multiple access (GF-NOMA) is a potential multiple access
framework for short-packet internet-of-things (IoT) networks to enhance connectivity …
framework for short-packet internet-of-things (IoT) networks to enhance connectivity …
When UAVs meet cognitive radio: Offloading traffic under uncertain spectrum environment via deep reinforcement learning
The emerging Internet of Things (IoT) paradigm makes our telecommunications networks
increasingly congested. Unmanned aerial vehicles (UAVs) have been regarded as a …
increasingly congested. Unmanned aerial vehicles (UAVs) have been regarded as a …
Deep learning-based flexible joint channel estimation and signal detection of multi-user OFDM-NOMA
This paper proposes a deep learning (DL)-based joint channel estimation and signal
detection in multi-user orthogonal-frequency division multiplexing-non-orthogonal multiple …
detection in multi-user orthogonal-frequency division multiplexing-non-orthogonal multiple …