相关论文: Proactive Traffic Offloading in Dynamic Integrated…
Opportunistic mobile networks consisting of intermittently connected mobile devices have been exploited for various applications, such as computational offloading and mitigating cellular traffic load. In contrast to existing work, in this…
The convergence of the Internet of vehicles (IoV) and 6G networks is driving the evolution of next-generation intelligent transportation systems. However, IoV networks face persistent challenges, including low spectral efficiency in…
Machine-to-machine services are witnessing an unprecedented diffusion, which is expected to result in an ever-increasing data traffic load. In this context, satellite technology is playing a pivotal role, since it enables a widespread…
In Earth Observation Satellite Networks (EOSNs) with a large number of battery-carrying satellites, proper power allocation and task scheduling are crucial to improving the data offloading efficiency. As such, we jointly optimize power…
To enable mobility in industrial communication systems, the seamless integration of 5G with Time-Sensitive Networking (TSN) is a promising approach. Deterministic communication across heterogeneous 5G-TSN systems requires joint scheduling…
Future wireless networks powered by renewable energy sources and storage systems (e.g., batteries) require energy-aware mechanisms to ensure stability in critical and high-demand scenarios. These include large-scale user gatherings,…
In the evolving landscape of vertical heterogeneous networks, the practice of cell switching particularly for small base stations faces a significant challenge due to the lack of accurate data on the traffic load of sleeping SBSs. This…
Fully re-orientable small spacecraft are now supported by commercial technologies, allowing them to point their instruments in any direction and capture images, with short notice. When combined with improved onboard processing, and…
With the rapid development of sixth-generation (6G) communication technology, global communication networks are moving towards the goal of comprehensive and seamless coverage. In particular, low earth orbit (LEO) satellites have become a…
With the rapid growth of mobile traffic demand, a promising approach to relieve cellular network congestion is to offload users' traffic to small-cell networks. In this paper, we investigate how the mobile users (MUs) can effectively…
Traffic forecasting is essential for the traffic construction of smart cities in the new era. However, traffic data's complex spatial and temporal dependencies make traffic forecasting extremely challenging. Most existing traffic…
Traffic flow forecasting has emerged as an indispensable mission for daily life, which is required to utilize the spatiotemporal relationship between each location within a time period under a graph structure to predict future flow.…
The rapid growth of computation-intensive applications like augmented reality, autonomous driving, remote healthcare, and smart cities has exposed the limitations of traditional terrestrial networks, particularly in terms of inadequate…
Scalability is a major challenge in non-geostationary orbit (NGSO) satellite networks due to the massive number of ground users sharing the limited sub-6 GHz spectrum. Using K- and higher bands is a promising alternative to increase the…
Load balancing is an effective approach to address the spatial-temporal fluctuation problem of mobile data traffic for cellular networks. The existing schemes that focus on channel borrowing from neighboring cells cannot be directly applied…
This study analyses the medium access control (MAC) layer aspects of a low-Earth-orbit (LEO) satellite-based Internet of Things (IoT) network. A transmission scheme based on change detection is proposed to accommodate more users within the…
The integrated satellite-terrestrial networks (ISTNs) through spectrum sharing have emerged as a promising solution to improve spectral efficiency and meet increasing wireless demand. However, this coexistence introduces significant…
Mobile traffic data in urban regions shows differentiated patterns during different hours of the day. The exploitation of these patterns enables highly accurate mobile traffic prediction for proactive network management. However, recent…
We develop an integrated Multi-Port Concurrent Communication Divisible Load Theory (MPCC-DLT) framework for relay-centric distributed satellite systems (DSS), capturing concurrent data dissemination, parallel computation, and result return…
This paper presents a novel framework for traffic prediction of IoT devices activated by binary Markovian events. First, we consider a massive set of IoT devices whose activation events are modeled by an On-Off Markov process with known…