Related papers: ITU-T Y.2325: NGN Evolution Towards Future
A novel paradigm of mobile edge generation (MEG)-enabled digital twin (DT) is proposed, which enables distributed on-device generation at mobile edge networks for real-time DT applications. First, an MEG-DT architecture is put forward to…
Building on the Ethernet Passive Optical Network (EPON) and Gigabit PON (GPON) standards, Next-Generation (NG) PONs (i) provide increased data rates, split ratios, wavelengths counts, and fiber lengths, as well as (ii) allow for all-optical…
As the explosive growth of smart devices and the advent of many new applications, traffic volume has been growing exponentially. The traditional centralized network architecture cannot accommodate such user demands due to heavy burden on…
Satellite networks are expected to support global connectivity and services via future integrated 6G space-terrestrial networks (STNs), as well as private non-geostationary satellite orbit (NGSO) constellations. In the past few years, many…
Next Generation Network (NGN) provides multimedia services over broadband based networks, which supports high definition TV (HDTV), and DVD quality video-on-demand content. The video services are thus seen as merging mainly three areas such…
The next generation of cellular networks is designed to provide ubiquitous connectivity to a wide range of devices. As Telecommunication Service Providers (TSPs) increasingly collaborate with public cloud providers to deploy 5G and beyond…
Graph Neural Networks (GNNs) is an architecture for structural data, and has been adopted in a mass of tasks and achieved fabulous results, such as link prediction, node classification, graph classification and so on. Generally, for a…
This paper discusses challenges and opportunities of considering the Metaverse as an Information-Centric Network (ICN). The Web today essentially represents a data-centric application layer: data named by URLs is manipulated with REST…
Networked control systems (NCSs), which are feedback control loops closed over a communication network, have been a popular research topic over the past decades. Numerous works in the literature propose novel algorithms and protocols with…
In disaster scenarios, ensuring both reliable communication and situational awareness becomes a critical challenge due to the partial or complete collapse of terrestrial networks. This paper proposes an integrated sensing and communication…
Natural language processing (NLP) is a key component of intelligent transportation systems (ITS), but it faces many challenges in the transportation domain, such as domain-specific knowledge and data, and multi-modal inputs and outputs.…
The evolution from Industry 4.0 to Industry 5.0 introduces stringent requirements for ultra reliable low latency communication (URLLC) to support human centric, intelligent, and resilient industrial systems. Sixth-generation (6G) wireless…
The growing interest in new applications involving co-located heterogeneous requirements, such as the Industrial Internet of Things (IIoT) paradigm, poses unprecedented challenges to the uplink wireless transmissions. Dedicated scheduling…
The ongoing deployment of 5G cellular systems is continuously exposing the inherent limitations of this system, compared to its original premise as an enabler for Internet of Everything applications. These 5G drawbacks are currently…
Future applications such as intelligent vehicles, the Internet of Things and holographic telepresence are already highlighting the limits of existing fifth-generation (5G) mobile networks. These limitations relate to data throughput,…
With a plethora of new connections, features, and services introduced, the 5th generation (5G) wireless technology reflects the development of mobile communication networks and is here to stay for the next decade. The multitude of services…
The current internet architecture is inefficient in fulfilling the demands of newly emerging internet applications. To address this issue, several over-the-top (OTT) application-level solutions have been employed, making the overall…
Graph Convolutional Network (GCN) has been widely applied in transportation demand prediction due to its excellent ability to capture non-Euclidean spatial dependence among station-level or regional transportation demands. However, in most…
The ever-increasing mobile data demands have posed significant challenges in the current radio access networks, while the emerging computation-heavy Internet of things (IoT) applications with varied requirements demand more flexibility and…
The future mobile networks facing many challenges and to cope these challenges, different standards and project has been proposed so far. Most recently Cognitive Networks has opened a new ground to present suitable architecture and…