The frontiers of deep reinforcement learning for resource management in future wireless HetNets: Techniques, challenges, and research directions
Next generation wireless networks are expected to be extremely complex due to their
massive heterogeneity in terms of the types of network architectures they incorporate, the …
massive heterogeneity in terms of the types of network architectures they incorporate, the …
A survey on integrated access and backhaul networks
Benefiting from the usage of the high-frequency band, utilizing part of the large available
bandwidth for wireless backhauling is feasible without considerable performance sacrifice …
bandwidth for wireless backhauling is feasible without considerable performance sacrifice …
[HTML][HTML] An intelligent resource allocation strategy with slicing and auction for private edge cloud systems
The convergence of transformative technologies, including the Internet of Things (IoT), Big
Data, and Artificial Intelligence (AI), has driven private edge cloud systems to the forefront of …
Data, and Artificial Intelligence (AI), has driven private edge cloud systems to the forefront of …
Short-term and long-term throughput maximization in mobile wireless-powered internet of things
With the evolution of Internet of Things (IoT), some IoT nodes possess a certain degree of
mobility, and the gains of the corresponding channels vary dramatically, incurring the energy …
mobility, and the gains of the corresponding channels vary dramatically, incurring the energy …
The prospect of reconfigurable intelligent surfaces in integrated access and backhaul networks
The Integrated Access and Backhaul (IAB) technology provides a new view of the
backhauling problem, especially when targeting end-to-end service provisioning. The IAB …
backhauling problem, especially when targeting end-to-end service provisioning. The IAB …
Learning from peers: Deep transfer reinforcement learning for joint radio and cache resource allocation in 5G RAN slicing
Network slicing is a critical technique for 5G communications that covers radio access
network (RAN), edge, transport and core slicing. The evolving network architecture requires …
network (RAN), edge, transport and core slicing. The evolving network architecture requires …
Hybrid machine-learning-based spectrum sensing and allocation with adaptive congestion-aware modeling in CR-assisted IoV networks
Unlicensed cognitive-radio (CR)-assisted Internet of Vehicles (IoV) users can access
licensed providers' radio spectrum and concurrently utilize the dedicated channel for data …
licensed providers' radio spectrum and concurrently utilize the dedicated channel for data …
Resource management for 5G NR integrated access and backhaul: A semi-centralized approach
The next generations of mobile networks will be deployed as ultra-dense networks, to match
the demand for increased capacity and the challenges that communications in the higher …
the demand for increased capacity and the challenges that communications in the higher …
Deep reinforcement learning for radio resource allocation and management in next generation heterogeneous wireless networks: A survey
Next generation wireless networks are expected to be extremely complex due to their
massive heterogeneity in terms of the types of network architectures they incorporate, the …
massive heterogeneity in terms of the types of network architectures they incorporate, the …
Detection tolerant black-box adversarial attack against automatic modulation classification with deep learning
Advances in adversarial attack and defense technologies will enhance the reliability of deep
learning (DL) systems spirally. Most existing adversarial attack methods make overly ideal …
learning (DL) systems spirally. Most existing adversarial attack methods make overly ideal …