Unsupervised machine learning for networking: Techniques, applications and research challenges
While machine learning and artificial intelligence have long been applied in networking
research, the bulk of such works has focused on supervised learning. Recently, there has …
research, the bulk of such works has focused on supervised learning. Recently, there has …
Symbol-level cross-technology communication via payload encoding
To mitigate the issue of cross-technology interference (CTI) under dense wireless, cross-
technology communication (CTC) was recently proposed, which enables direct …
technology communication (CTC) was recently proposed, which enables direct …
Mobility-aware load balancing for reliable self-organization networks: Multi-agent deep reinforcement learning
Abstract Self-Organizing Networks (SON) is a collection of functions for automatic
configuration, optimization, and healing of networks and mobility optimization is one of the …
configuration, optimization, and healing of networks and mobility optimization is one of the …
Load balancing by dynamic BBU-RRH map** in a self-optimised Cloud Radio Access Network
In this paper, a load-balancing scheme is investigated for C-RAN to optimise its performance
subject to physical resource limitation and users Quality of Service (QoS) demands …
subject to physical resource limitation and users Quality of Service (QoS) demands …
Exploiting the capacity-routing ability of a cloud radio access network
Network densification has become a dominant theme for capacity enhancement in cellular
networks. However, it increases the operational complexity and expenditure for mobile …
networks. However, it increases the operational complexity and expenditure for mobile …