This paper presents a comprehensive literature review on applications of deep
reinforcement learning (DRL) in communications and networking. Modern networks, eg …

The fifth generation (5G) mobile networks are envisioned to support the deluge of data traffic
with reduced energy consumption and improved quality of service (QoS) provision. To this …

Heterogeneous cellular networks can offload the mobile traffic and reduce the deployment
costs, which have been considered to be a promising technique in the next-generation …

This paper presents a tutorial on stochastic geometry (SG)-based analysis for cellular
networks. This tutorial is distinguished by its depth with respect to wireless communication …

This article proposes a novel multiagent deep reinforcement learning-based algorithm which
can realize federated learning (FL) computation with Internet-of-Underwater-Things (IoUT) …

With the rapid development of future wireless communication, the combination of NOMA
technology and millimeter-wave (mmWave) technology has become a research hotspot. The …

Cyber‐physical systems (CPS) help create new services and applications by revolutionising
our world in different fields through their tight interactions and automated decisions. This is …

The problem of joint downlink cell association (CA) and wireless backhaul bandwidth
allocation (WBBA) in two-tier cellular heterogeneous networks (HetNets) is investigated …

In wireless heterogeneous networks (HetNets), the spatial densification through small cells
and the application of massive MIMO antenna arrays are key enablers for high data …

Horizontal and vertical handoffs are important ramifications of user mobility in multitier
heterogeneous wireless networks. They directly impact the signaling overhead and quality …