Applications of artificial intelligence and machine learning in smart cities
Smart cities are aimed to efficiently manage growing urbanization, energy consumption,
maintain a green environment, improve the economic and living standards of their citizens …
maintain a green environment, improve the economic and living standards of their citizens …
6G enabled smart infrastructure for sustainable society: Opportunities, challenges, and research roadmap
The 5G wireless communication network is currently faced with the challenge of limited data
speed exacerbated by the proliferation of billions of data-intensive applications. To address …
speed exacerbated by the proliferation of billions of data-intensive applications. To address …
LightAMC: Lightweight automatic modulation classification via deep learning and compressive sensing
Automatic modulation classification (AMC) is an promising technology for non-cooperative
communication systems in both military and civilian scenarios. Recently, deep learning (DL) …
communication systems in both military and civilian scenarios. Recently, deep learning (DL) …
Fast beamforming design via deep learning
H Huang, Y Peng, J Yang, W Xia… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Beamforming is considered as one of the most important techniques for designing advanced
multiple-input and multiple-output (MIMO) systems. Among existing design criterions, sum …
multiple-input and multiple-output (MIMO) systems. Among existing design criterions, sum …
Deep reinforcement learning for dynamic uplink/downlink resource allocation in high mobility 5G HetNet
Recently, the 5G is widely deployed for supporting communications of high mobility nodes
including train, vehicular and unmanned aerial vehicles (UAVs) largely emerged as the …
including train, vehicular and unmanned aerial vehicles (UAVs) largely emerged as the …
Deep learning for B5G open radio access network: Evolution, survey, case studies, and challenges
Open Radio Access Network (O-RAN) alliance was recently launched to devise a new RAN
architecture featuring open, software-driven, virtual, and intelligent radio access architecture …
architecture featuring open, software-driven, virtual, and intelligent radio access architecture …
Deep learning-based mmWave beam selection for 5G NR/6G with sub-6 GHz channel information: Algorithms and prototype validation
In fifth-generation (5G) communications, millimeter wave (mmWave) is one of the key
technologies to increase the data rate. To overcome this technology's poor propagation …
technologies to increase the data rate. To overcome this technology's poor propagation …
Model-driven deep learning based channel estimation and feedback for millimeter-wave massive hybrid MIMO systems
X Ma, Z Gao, F Gao, M Di Renzo - IEEE Journal on Selected …, 2021 - ieeexplore.ieee.org
This paper proposes a model-driven deep learning (MDDL)-based channel estimation and
feedback scheme for wideband millimeter-wave (mmWave) massive hybrid multiple-input …
feedback scheme for wideband millimeter-wave (mmWave) massive hybrid multiple-input …
Deep learning for massive MIMO uplink detectors
MA Albreem, AH Alhabbash… - … Surveys & Tutorials, 2021 - ieeexplore.ieee.org
Detection techniques for massive multiple-input multiple-output (MIMO) have gained a lot of
attention in both academia and industry. Detection techniques have a significant impact on …
attention in both academia and industry. Detection techniques have a significant impact on …
Enabling AI in future wireless networks: A data life cycle perspective
Recent years have seen rapid deployment of mobile computing and Internet of Things (IoT)
networks, which can be mostly attributed to the increasing communication and sensing …
networks, which can be mostly attributed to the increasing communication and sensing …