相关论文: LightningNet: Distributed Graph-based Cellular Net…

Future networks, such as 6G, will need to support a vast and diverse range of interconnected devices and applications, each with its own set of requirements. While traditional network management approaches will suffice, an automated…

This paper derives tight performance upper and lower bounds on the downlink outage efficiency of K-tier heterogeneous cellular networks (HCNs) for general signal propagation models with Poisson distributed base stations in each tier. In…

We present a framework for simulating signal propagation in geometric networks (i.e. networks that can be mapped to geometric graphs in some space) and for developing algorithms that estimate (i.e. map) the state and functional topology of…

A two-tier heterogeneous cellular network (HCN) with intra-tier and inter-tier dependence is studied. The macro cell deployment follows a Poisson point process (PPP) and two different clustered point processes are used to model the…

In the near future, Internet-of-Things (IoT) is expected to connect billions of devices (e.g., smartphones and sensors), which generate massive real-time data at the network edge. Intelligence can be distilled from the data to support…

Hybrid light fidelity (LiFi) and wireless fidelity (WiFi) networks are a promising paradigm of heterogeneous network (HetNet), attributed to the complementary physical properties of optical spectra and radio frequency. However, the current…

Edge computing is a promising approach for localized data processing for many edge applications and systems including Internet of Things (IoT), where computationally intensive tasks in IoT devices could be divided into sub-tasks and…

Sharing forecasts of network timeseries data, such as cellular or electricity load patterns, can improve independent control applications ranging from traffic scheduling to power generation. Typically, forecasts are designed without…

Carrier aggregation, which allows users to aggregate several component carriers to obtain up to 100 MHz of band- width, is one of the central features envisioned for next generation cellular networks. While this feature will enable support…

We define and propose a resource allocation architecture for cellular networks. The architecture combines content-aware, time-aware and location-aware resource allocation for next generation broadband wireless systems. The architecture…

Future cellular networks will sustainably integrate computing, intelligence and services within a network of networks ecosystem that includes IoT devices and subnetworks for local communications and distributed processing. This integration…

Weather forecasting is an essential task to tackle global climate change. Weather forecasting requires the analysis of multivariate data generated by heterogeneous meteorological sensors. These sensors comprise of ground-based sensors,…

The mobile edge computing (MEC) has been introduced for providing computing capabilities at the edge of networks to improve the latency performance of wireless networks. In this paper, we provide the novel framework for MEC-enabled…

This paper proposes a spatiotemporal graph neural network-based performance prediction algorithm to address the challenge of forecasting performance fluctuations in distributed backend systems with multi-level service call structures. The…

Traditional cellular traffic forecasting models are optimized for minimizing symmetric errors, leaving them indifferent to shifting operational priorities. To bridge this gap, we introduce BERTO, a BERT-based framework for traffic…

In today's day and age, a mobile phone has become a basic requirement needed for anyone to thrive. With the cellular traffic demand increasing so dramatically, it is now necessary to accurately predict the user traffic in cellular networks,…

Efficiently solving unbalanced three-phase power flow in distribution grids is pivotal for grid analysis and simulation. There is a pressing need for scalable algorithms capable of handling large-scale unbalanced power grids that can…

It is crucial for the service provider to comprehend and forecast mobile traffic in large-scale cellular networks in order to govern and manage mechanisms for base station placement, load balancing, and network planning. The purpose of this…

This paper presents a detailed study of how graph neural networks can be used on edge intelligent meters in a microgrid to forecast photovoltaic power generation. The problem background and the adopted technologies are introduced, including…

Vehicle flow, a crucial indicator for transportation, is often limited by detector coverage. With the advent of extensive mobile network coverage, we can leverage mobile user activities, or cellular traffic, on roadways as a proxy for…