Caching transient data for Internet of Things: A deep reinforcement learning approach
Connected devices in Internet-of-Things (IoT) continuously generate enormous amount of
data, which is transient and would be requested by IoT application users, such as …
data, which is transient and would be requested by IoT application users, such as …
Deep learning-based long-term power allocation scheme for NOMA downlink system in S-IoT
In this paper, we formulate a long-term resource allocation problem of non-orthogonal
multiple access (NOMA) downlink system for the satellite-based Internet of Things (S-IoT) to …
multiple access (NOMA) downlink system for the satellite-based Internet of Things (S-IoT) to …
DeepEdge: A new QoE-based resource allocation framework using deep reinforcement learning for future heterogeneous edge-IoT applications
Edge computing is emerging to empower the future of Internet of Things (IoT) applications.
However, due to heterogeneity of applications, it is a significant challenge for the edge cloud …
However, due to heterogeneity of applications, it is a significant challenge for the edge cloud …
Deep-reinforcement-learning-based spectrum resource management for industrial Internet of Things
The Industrial Internet of Things (IIoT) has attracted tremendous interest from both industry
and academia as it can significantly improve production efficiency and system intelligence …
and academia as it can significantly improve production efficiency and system intelligence …
Artificial intelligence powered mobile networks: From cognition to decision
Mobile networks (MNs) are anticipated to provide unprecedented opportunities to enable a
new world of connected experiences and radically shift the way people interact with …
new world of connected experiences and radically shift the way people interact with …
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 …
Resource allocation for NOMA-MEC systems in ultra-dense networks: A learning aided mean-field game approach
Attracted by the advantages of multi-access edge computing (MEC) and non-orthogonal
multiple access (NOMA), this article studies the resource allocation problem of a NOMA …
multiple access (NOMA), this article studies the resource allocation problem of a NOMA …
Analysis of the narrow band internet of things (NB-IoT) technology
KK Nair, AM Abu-Mahfouz… - 2019 conference on …, 2019 - ieeexplore.ieee.org
Internet of Things (IoT) has the potential to enable the interconnection of small foot-print
devices, which can offer valuable information for various critical use cases. It is expected to …
devices, which can offer valuable information for various critical use cases. It is expected to …
Computation offloading with multiple agents in edge-computing–supported IoT
With the development of the Internet of Things (IoT) and the birth of various new IoT devices,
the capacity of massive IoT devices is facing challenges. Fortunately, edge computing can …
the capacity of massive IoT devices is facing challenges. Fortunately, edge computing can …
Live data analytics with collaborative edge and cloud processing in wireless IoT networks
Recently, big data analytics has received important attention in a variety of application
domains including business, finance, space science, healthcare, telecommunication and …
domains including business, finance, space science, healthcare, telecommunication and …