Related papers: Digital Twin Synchronization Over Mobile Embodied …
In modern wireless network architectures, such as O-RAN, artificial intelligence (AI)-based applications are deployed at intelligent controllers to carry out functionalities like scheduling or power control. The AI "apps" are selected on…
Optical communication is developing rapidly in the directions of hardware resource diversification, transmission system flexibility, and network function virtualization. Its proliferation poses a significant challenge to traditional optical…
Agentic AI represents a new paradigm for automating complex systems by using Large AI Models (LAMs) to provide human-level cognitive abilities with multimodal perception, planning, memory, and reasoning capabilities. This will lead to a new…
Digital twin (DT) is one of the most promising enabling technologies for realizing smart grids. Characterized by seamless and active---data-driven, real-time, and closed-loop---integration between digital and physical spaces, a DT is much…
A transportation digital twin represents a digital version of a transportation physical object or process, such as a traffic signal controller, and thereby a two-way real-time data exchange between the physical twin and digital twin. This…
The proliferation of 5G technology necessitates advanced network management strategies to ensure optimal performance and reliability. Digital Twin (DT)s have emerged as a promising paradigm for modeling and simulating complex systems like…
In this paper, we investigate an accurate synchronization between a physical network and its digital network twin (DNT), which serves as a virtual representation of the physical network. The considered network includes a set of base…
The concept of a digital twin (DT) plays a pivotal role in the ongoing digital transformation and has achieved significant strides for various wireless applications in recent years. In particular, the field of autonomous vehicles is a…
Digital Twins (DTs) for physical wireless environments have been recently proposed as accurate virtual representations of the propagation environment that can enable multi-layer decisions at the physical communication equipment. At…
In this paper, we introduce a first-of-its-kind forecasting-driven, incentive-inherent service provisioning framework for distributed air-ground integrated networks that explicitly accounts for human-machine coexistence. In our framework,…
Aligning agentic AI with user intent is critical for delegating complex, socially embedded tasks, yet user preferences are often implicit, evolving, and difficult to specify upfront. We present DoubleAgents, a system for human-agent…
Effective channel estimation in sparse and high-dimensional environments is essential for next-generation wireless systems, particularly in large-scale MIMO deployments. This paper introduces a novel framework that leverages digital twins…
Wi-Fi networks increasingly suffer from performance degradation caused by contention-based channel access, dense deployments, and largely self-managed operation among mutually interfering access points (APs). In this paper, we propose a…
In existing wireless networks, the control programs have been designed manually and for certain predefined scenarios. This process is complicated and error-prone, and the resulting control programs are not resilient to disruptive changes.…
Recent advances in intelligent network control have primarily relied on task-specific Artificial Intelligence (AI) models deployed separately within the Radio Access Network (RAN) and Core Network (CN). While effective for isolated models,…
Virtual models of human gait, or digital twins, offer a promising solution for studying mobility without the need for labor-intensive data collection. However, challenges such as the sim-to-real gap and limited adaptability to diverse…
With the rapid development of deep reinforcement learning technology, it gradually demonstrates excellent potential and is becoming the most promising solution in the robotics. However, in the smart manufacturing domain, there is still not…
Generative AI (GenAI) has transformed applications in natural language processing and content creation, yet centralized inference remains hindered by high latency, limited customizability, and privacy concerns. Deploying large models (LMs)…
The dramatic increase in the connectivity demand results in an excessive amount of Internet of Things (IoT) sensors. To meet the management needs of these large-scale networks, such as accurate monitoring and learning capabilities, Digital…
Agentic artificial intelligence (AI) is emerging as a key enabler for autonomous radio access networks (RANs), where multiple large language model (LLM)-based agents reason and collaborate to achieve operator-defined intents. The open RAN…