27 citations · 86 across the 13 of their papers we have counts for
8 papers · 1 filter
TinyQMIX: Distributed Access Control for mMTC via Multi-agent Reinforcement Learning
Tien Thanh Le, Yusheng Ji, John C. S Lui
Distributed access control is a crucial component for massive machine type communication (mMTC). In this communication scenario, centralized resource allocation is not scalable bec…
Resource Awareness in Unmanned Aerial Vehicle-Assisted Mobile-Edge Computing Systems
Xianfu Chen, Tao Chen, Zhifeng Zhao +3
This paper investigates an unmanned aerial vehicle (UAV)-assisted mobile-edge computing (MEC) system, in which the UAV provides complementary computation resource to the terrestria…
Understanding the Modeling of Computer Network Delays using Neural Networks
Albert Mestres, Eduard Alarcón, Yusheng Ji +1
Recent trends in networking are proposing the use of Machine Learning (ML) techniques for the control and operation of the network. In this context, ML can be used as a computer ne…
Multipath Transmission Scheduling in Millimeter Wave Cloud Radio Access Networks
Xianfu Chen, Pei Liu, Hang Liu +2
Millimeter wave (mmWave) communications provide great potential for next-generation cellular networks to meet the demands of fast-growing mobile data traffic with plentiful spectru…
Performance Optimization in Mobile-Edge Computing via Deep Reinforcement Learning
Xianfu Chen, Honggang Zhang, Celimuge Wu +3
To improve the quality of computation experience for mobile devices, mobile-edge computing (MEC) is emerging as a promising paradigm by providing computing capabilities within radi…
SDN for End-Nodes: Scenario Analysis and Architectural Guidelines
Alberto Rodriguez-Natal, Vina Ermagan, Kien Nguyen +4
The advent of SDN has brought a plethora of new architectures and controller designs for many use-cases and scenarios. Existing SDN deployments focus on campus, datacenter and WAN…
Skolem Sequence Based Self-adaptive Broadcast Protocol in Cognitive Radio Networks
Lin Chen, Zhiping Xiao, Kaigui Bian +3
The base station (BS) in a multi-channel cognitive radio (CR) network has to broadcast to secondary (or unlicensed) receivers/users on more than one broadcast channels via channel…
Optimizing Average-Maximum TTR Trade-off for Cognitive Radio Rendezvous
Lin Chen, Shuyu Shi, Kaigui Bian +1
In cognitive radio (CR) networks, "TTR", a.k.a. time-to-rendezvous, is one of the most important metrics for evaluating the performance of a channel hopping (CH) rendezvous protoco…