A federated reinforcement learning framework for incumbent technologies in beyond 5G networks
Incumbent wireless technologies for futuristic fifth generation (5G) and beyond 5G (B5G)
networks, such as IEEE 802.11 ax (WiFi), are vital to provide ubiquitous ultra-reliable and …
networks, such as IEEE 802.11 ax (WiFi), are vital to provide ubiquitous ultra-reliable and …
Intelligent sharing for LTE and WiFi systems in unlicensed bands: A deep reinforcement learning approach
Operating LTE networks in unlicensed bands together with legacy WiFi systems is deemed
as a promising technique to support explosively growing mobile traffic. In conventional …
as a promising technique to support explosively growing mobile traffic. In conventional …
Reinforcement learning meets wireless networks: A layering perspective
Driven by the soaring traffic demand and the growing diversity of mobile services, wireless
networks are evolving to be increasingly dense and heterogeneous. Accordingly, in such …
networks are evolving to be increasingly dense and heterogeneous. Accordingly, in such …
Deep reinforcement learning for mobile 5G and beyond: Fundamentals, applications, and challenges
Future-generation wireless networks (5G and beyond) must accommodate surging growth in
mobile data traffic and support an increasingly high density of mobile users involving a …
mobile data traffic and support an increasingly high density of mobile users involving a …
Deep reinforcement learning paradigm for dense wireless networks in smart cities
Wireless local area networks (WLANs) are widely deployed for Internet-centric data
applications. Due to their extensive norm in our day-to-day wireless-enabled life, WLANs are …
applications. Due to their extensive norm in our day-to-day wireless-enabled life, WLANs are …
Reinforcement-learning-enabled massive internet of things for 6G wireless communications
Recently, extensive research efforts have been devoted to developing beyond fifth
generation (B5G), also referred to as sixth generation (6G) wireless networks aimed at …
generation (B5G), also referred to as sixth generation (6G) wireless networks aimed at …
Machine learning for 5G/B5G mobile and wireless communications: Potential, limitations, and future directions
Driven by the demand to accommodate today's growing mobile traffic, 5G is designed to be
a key enabler and a leading infrastructure provider in the information and communication …
a key enabler and a leading infrastructure provider in the information and communication …
When cellular meets WiFi in wireless small cell networks
The deployment of small cell base stations, SCBSs, overlaid on existing macrocellular
systems is seen as a key solution for offloading traffic, optimizing coverage, and boosting the …
systems is seen as a key solution for offloading traffic, optimizing coverage, and boosting the …
[PDF][PDF] Deep learning for proactive resource allocation in LTE-U networks
LTE in unlicensed spectrum (LTE-U) is a promising approach to overcome the wireless
spectrum scarcity. However, to reap the benefits of LTE-U, a fair coexistence mechanism …
spectrum scarcity. However, to reap the benefits of LTE-U, a fair coexistence mechanism …
Enhancing WiFi multiple access performance with federated deep reinforcement learning
Carrier sensing multiple access/collision avoidance (CSMA/CA) is the backbone MAC
protocol for IEEE 802.11 networks. However, tuning the binary exponential back-off (BEB) …
protocol for IEEE 802.11 networks. However, tuning the binary exponential back-off (BEB) …