Related papers: A Comparative Study of Location Management Schemes…
Fine-tuning is the process of adapting the pre-trained large language models (LLMs) for downstream tasks. Due to substantial parameters, fine-tuning LLMs on mobile devices demands considerable memory resources, and suffers from high…
Multi-tier cellular networks are considered as an effective solution to enhance the coverage and data rate offered by cellular systems. In a multi-tier network, high power base stations (BSs) such as macro BSs are overlaid by lower power…
Location distinction is defined as determining whether or not the position of a device has changed. We introduce methods and metrics for performing location distinction in multiple-input multiple-output (MIMO) wireless networks. Using MIMO…
Localization is one of the most important factor in wireless sensor networks as many applications demand position information of sensors. Recently there is an increasing interest on the use of mobile anchors for localizing sensors. Most of…
A key challenge in transportation planning is that the collective preferences of heterogeneous travelers often diverge from the policies produced by model-driven decision tools. This misalignment frequently results in implementation delays…
AI agents based on multimodal large language models (LLMs) are expected to revolutionize human-computer interaction and offer more personalized assistant services across various domains like healthcare, education, manufacturing, and…
The positioning of users using their smartphones represents interesting service for various areas. Position of users can represent valuable information for various service providers. In industry 4.0 smart devices such as smartphone or…
The LP WAN networks use gateways or base stations to communicate with devices distributed on large distances, up to tens of kilometres. The selection of optimal gateway locations in wireless networks should allow providing the complete…
A new research problem named configuration learning is described in this work. A novel algorithm is proposed to address the configuration learning problem. The configuration learning problem is defined to be the optimization of the Machine…
We present a scalable solution to link entities across mobility datasets using their spatio-temporal information. This is a fundamental problem in many applications such as linking user identities for security, understanding privacy…
Location and mobility patterns of individuals are important to environmental planning, societal resilience, public health, and a host of commercial applications. Mining telecommunication traffic and transactions data for such purposes is…
By virtue of its great utility in solving real-world problems, optimization modeling has been widely employed for optimal decision-making across various sectors, but it requires substantial expertise from operations research professionals.…
Large Language Models (LLMs) are poised to play an increasingly important role in our lives, providing assistance across a wide array of tasks. In the geospatial domain, LLMs have demonstrated the ability to answer generic questions, such…
A novel multi-scale temporal convolutional network (TCN) and long short-term memory network (LSTM) based magnetic localization approach is proposed. To enhance the discernibility of geomagnetic signals, the time-series preprocessing…
Train delays can propagate rapidly throughout the Urban Rail Transit (URT) network under networked operation conditions, posing significant challenges to operational departments. Accurately predicting passenger travel choices under train…
Training large language models (LLMs), and other large machine learning models, involves repeated communication of large volumes of data across a data center network. The communication patterns induced by these training process exhibit high…
Beam management is central in the operation of beamformed wireless cellular systems such as 5G New Radio (NR) networks. Focusing the energy radiated to mobile terminals (MTs) by increasing the number of beams per cell increases signal power…
In this paper, we study and present a management and orchestration framework for vehicular communications, which enables service continuity for the vehicle via an optimized application-context relocation approach. To optimize the transfer…
In large-scale wireless networks such as mobile ad hoc and sensor networks, efficient and robust service discovery and data-access mechanisms are both essential and challenging. Rendezvous-based mechanisms provide a valuable solution for…
Position-based routing protocols take advantage of location information to perform a stateless and efficient routing. To enable position-based routing, a node must be able to discover the location of the messages' destination node. This…