Towards energy efficient 5G networks using machine learning: Taxonomy, research challenges, and future research directions
As the world pushes toward the use of greener technology and minimizes energy waste,
energy efficiency in the wireless network has become more critical than ever. The next …
energy efficiency in the wireless network has become more critical than ever. The next …
Application of reinforcement learning and deep learning in multiple-input and multiple-output (MIMO) systems
The current wireless communication infrastructure has to face exponential development in
mobile traffic size, which demands high data rate, reliability, and low latency. MIMO systems …
mobile traffic size, which demands high data rate, reliability, and low latency. MIMO systems …
Multi-hop RIS-empowered terahertz communications: A DRL-based hybrid beamforming design
Wireless communication in the TeraHertz band (0.1-10 THz) is envisioned as one of the key
enabling technologies for the future sixth generation (6G) wireless communication systems …
enabling technologies for the future sixth generation (6G) wireless communication systems …
Reconfigurable intelligent surface assisted multiuser MISO systems exploiting deep reinforcement learning
Recently, the reconfigurable intelligent surface (RIS), benefited from the breakthrough on the
fabrication of programmable meta-material, has been speculated as one of the key enabling …
fabrication of programmable meta-material, has been speculated as one of the key enabling …
Deep learning for mmWave beam and blockage prediction using sub-6 GHz channels
M Alrabeiah, A Alkhateeb - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Predicting the millimeter wave (mmWave) beams and blockages using sub-6 GHz channels
has the potential of enabling mobility and reliability in scalable mmWave systems. Prior work …
has the potential of enabling mobility and reliability in scalable mmWave systems. Prior work …
Pervasive machine learning for smart radio environments enabled by reconfigurable intelligent surfaces
GC Alexandropoulos, K Stylianopoulos… - Proceedings of the …, 2022 - ieeexplore.ieee.org
The emerging technology of reconfigurable intelligent surfaces (RISs) is provisioned as an
enabler of smart wireless environments, offering a highly scalable, low-cost, hardware …
enabler of smart wireless environments, offering a highly scalable, low-cost, hardware …
Millimeter wave base stations with cameras: Vision-aided beam and blockage prediction
M Alrabeiah, A Hredzak… - 2020 IEEE 91st vehicular …, 2020 - ieeexplore.ieee.org
This paper investigates a novel research direction that leverages vision to help overcome
the critical wireless communication challenges. In particular, this paper considers millimeter …
the critical wireless communication challenges. In particular, this paper considers millimeter …
Deep reinforcement learning for intelligent reflecting surfaces: Towards standalone operation
The promising coverage and spectral efficiency gains of intelligent reflecting surfaces (IRSs)
are attracting increasing interest. To adopt these surfaces in practice, however, several …
are attracting increasing interest. To adopt these surfaces in practice, however, several …
Deep transfer learning-based downlink channel prediction for FDD massive MIMO systems
Artificial intelligence (AI) based downlink channel state information (CSI) prediction for
frequency division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems …
frequency division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems …
Deep learning for large intelligent surfaces in millimeter wave and massive MIMO systems
A Taha, M Alrabeiah… - 2019 IEEE Global …, 2019 - ieeexplore.ieee.org
As a promising candidate for future wireless systems, large intelligent surfaces (LISs)
recently emerged to serve considerate improvements in both spectral and energy …
recently emerged to serve considerate improvements in both spectral and energy …