Kyung Hee University · 工学
Professor Yan Kyaw Tun's research lab specializes in next-generation wireless communication and edge computing systems, focusing on UAV-aided mobile edge computing, network slicing in 5G/6G networks, and integrated space-air-ground networks. The lab investigates energy-efficient task offloading, resource allocation, and collaborative computing architectures to enhance network performance and support diverse services such as IoT, eMBB, and URLLC. A key emphasis is placed on optimizing latency, energy consumption, and network capacity in dynamic and infrastructure-scarce environments.
Figures are computed from collected data and may differ slightly.
Unmanned aerial vehicles (UAVs) have been deployed to enhance the network capacity and provide services to mobile users with or without infrastructure coverage. At the same time, we have observed the exponential growth in Internet of Things (IoTs) devices and applications. However, as IoT devices have limited computation capacity and battery lifetime, it is challenging to process data locally on the devices. To this end, in this letter, a UAV-aided mobile edge computing system is proposed. The p
Wireless network slicing (i.e., network virtualization) is one of the potential technologies for addressing the issue of rapidly growing demand in mobile data services related to 5G cellular networks. It logically decouples the current cellular networks into two entities: infrastructure providers (InPs) and mobile virtual network operators (MVNOs). The resources of base stations (e.g., resource blocks, transmission power, and antennas), which are owned by the InP, are shared with multiple MVNOs
Recently, unmanned aerial vehicles (UAVs)-assisted multi-access edge computing (MEC) systems emerged as a promising solution for providing computation services to mobile users outside of terrestrial infrastructure coverage. As each UAV operates independently, however, it is challenging to meet the computation demands of the mobile users due to the limited computing capacity at the UAV’s MEC server as well as the UAV’s energy constraint. Therefore, collaboration among UAVs is needed. In this arti
Multi-access edge computing (MEC) enables mobile users to offload their computation tasks to the server located at the edge of the cellular network. Thereby, MEC prolongs the battery lifespan of mobile devices and significantly enhances their computation capacities. However, a significant challenge is to offload the computation tasks to the MEC server in an energy-efficient manner. Meanwhile, in the fifth-generation (5G) networks, mobile users with different service requirements classified as en
Multi-access edge computing (MEC)-enabled integrated space-air-ground networks have drawn much attention recently, as they can provide communication and computing services to wireless devices in areas that lack terrestrial base stations (TBSs). They could make it possible for battery-powered Internet of Things (IoT) devices to offload their computation tasks to MEC-enabled unmanned aerial vehicles (UAVs) assisted aerial networks and low earth orbit (LEO) satellites and thus reduce their energy c
An efficient content caching policy at the edge of the mobile cellular network can improve the quality of services of the mobile users and reduces network congestion at the backhaul. On the other hand, the wireless network virtualization emerges as a cutting-edge technique to address the limited network capacity problem due to the exponential growth of the mobile data traffic. In addition, the wireless network virtualization can bring huge benefits such as reducing the capital expenditure (CAPEX
Unmanned aerial vehicles (UAVs) are widely deployed to enhance the wireless network capacity and to provide communication services to mobile users beyond the infrastructure coverage. Recently, with the help of a promising technology called network virtualization, multiple service providers (SPs) can share the infrastructures and wireless resources owned by the mobile network operators (MNOs). Then, they provide specific services to their mobile users using the resources obtained from MNOs. Howev
With the help of multi-access edge computing (MEC) system, traditional mobile network operators (MNOs) can provide various services to their mobile users with the minimum delay by installing micro-datacenters at the base stations (BSs)(i.e., at the edge of the radio access network). However, the capital and operational expenditures become significant challenge for the MNOs. Fortunately, multiple MNOs can coexist on the same infrastructure and share the network resources with the help of upcoming
Multi-access edge computing (MEC)-enabled integrated space-air-ground (SAG) networks have drawn much attention recently, as they can provide communication and computing services to wireless devices in areas that lack terrestrial base stations (TBSs). Leveraging the ample bandwidth in the terahertz (THz) spectrum, in this paper, we propose MEC-enabled integrated SAG networks with collaboration among unmanned aerial vehicles (UAVs). We then formulate the problem of minimizing the energy consumptio
Virtualized wireless networks is one of the techniques to satisfy the increasing demand of mobile data services and for future wireless network. Nework virtualization enables efficient resource utilization and it also reduces capital expenditures and operational expenditures of mobile network operators (MNOs). In this paper, we present virtualized wireless network where users of each service provider (SP) are served by an infrastructure provider (InP) who owns a set eNBs. We propose the problem
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