Proactive resource management for LTE in unlicensed spectrum: A deep learning perspective
Performing cellular long term evolution (LTE) communications in unlicensed spectrum using
licensed assisted access LTE (LTE-LAA) is a promising approach to overcome wireless …
licensed assisted access LTE (LTE-LAA) is a promising approach to overcome wireless …
Multiaccess point coordination for next-gen Wi-Fi networks aided by deep reinforcement learning
Wi-Fi in the enterprise—characterized by overlapping Wi-Fi cells—constitutes the design
challenge for next-generation networks. Standardization for recently started IEEE 802.11 be …
challenge for next-generation networks. Standardization for recently started IEEE 802.11 be …
Accelerating reinforcement learning via predictive policy transfer in 6g ran slicing
AM Nagib, H Abou-Zeid… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Reinforcement Learning (RL) algorithms have recently been proposed to solve dynamic
radio resource management (RRM) problems in beyond 5G networks. However, RL-based …
radio resource management (RRM) problems in beyond 5G networks. However, RL-based …
WiFederated: Scalable WiFi sensing using edge-based federated learning
SM Hernandez, E Bulut - IEEE Internet of Things Journal, 2021 - ieeexplore.ieee.org
WiFi sensing using channel state information (CSI) offers a device-free and nonintrusive
method for human activity monitoring. However, the data-hungry and location-specific …
method for human activity monitoring. However, the data-hungry and location-specific …
[HTML][HTML] Machine learning in beyond 5G/6G networks—State-of-the-art and future trends
Artificial Intelligence (AI) and especially Machine Learning (ML) can play a very important
role in realizing and optimizing 6G network applications. In this paper, we present a brief …
role in realizing and optimizing 6G network applications. In this paper, we present a brief …
Applications of deep reinforcement learning in communications and networking: A survey
This paper presents a comprehensive literature review on applications of deep
reinforcement learning (DRL) in communications and networking. Modern networks, eg …
reinforcement learning (DRL) in communications and networking. Modern networks, eg …
Reinforcement learning based load balancing for hybrid LiFi WiFi networks
Light fidelity (LiFi) is an emerging communication technology, which utilizes the light-
emitting diodes (LEDs) for high-speed wireless communications. Due to its huge unlicensed …
emitting diodes (LEDs) for high-speed wireless communications. Due to its huge unlicensed …
Applications of multi-agent reinforcement learning in future internet: A comprehensive survey
Future Internet involves several emerging technologies such as 5G and beyond 5G
networks, vehicular networks, unmanned aerial vehicle (UAV) networks, and Internet of …
networks, vehicular networks, unmanned aerial vehicle (UAV) networks, and Internet of …
Context-aware indoor VLC/RF heterogeneous network selection: Reinforcement learning with knowledge transfer
For the converged use of LTE, WLAN, and visible light communication in indoor scenarios,
fine-grained and intelligent network selection is essential for ensuring high user quality of …
fine-grained and intelligent network selection is essential for ensuring high user quality of …
[HTML][HTML] Coexistence scheme for uncoordinated LTE and WiFi networks using experience replay based Q-learning
Nowadays, broadband applications that use the licensed spectrum of the cellular network
are growing fast. For this reason, Long-Term Evolution-Unlicensed (LTE-U) technology is …
are growing fast. For this reason, Long-Term Evolution-Unlicensed (LTE-U) technology is …