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Network digital twin (NDT) models are virtual models that replicate the behavior of physical communication networks and are considered a key technology component to enable novel features and capabilities in future 6G networks. In this work,…
Digital twins (DTs) have driven major advancements across various industrial domains over the past two decades. With the rapid advancements in autonomous driving and vehicle-to-everything (V2X) technologies, integrating DTs into vehicular…
In this paper, the problem of low-latency communication and computation resource allocation for digital twin (DT) over wireless networks is investigated. In the considered model, multiple physical devices in the physical network (PN) needs…
Digital network twins (DNTs) are virtual representations of physical networks, designed to enable real-time monitoring, simulation, and optimization of network performance. When integrated with machine learning (ML) techniques, particularly…
In this paper, we investigate a novel digital network twin (DNT) assisted deep learning (DL) model training framework. In particular, we consider a physical network where a base station (BS) uses several antennas to serve multiple mobile…
In the 6G era, integrating Mobile Edge Computing (MEC) and Digital Twin (DT) technologies presents a transformative approach to enhance network performance through predictive, adaptive control for energy-efficient, low-latency…
Next-generation (NextG) wireless networks are expected to require intelligent, scalable, and context-aware radio resource management (RRM) to support ultra-dense deployments, diverse service requirements, and dynamic network conditions.…
Transportation Cyber-Physical Systems (T-CPS) enhance safety and mobility by integrating cyber and physical transportation systems. A key component of T-CPS is the Digital Twin (DT), a virtual representation that enables simulation,…
Digital Twins have emerged as a disruptive technology with great potential; they can enhance WDS by offering real-time monitoring, predictive maintenance, and optimization capabilities. This paper describes the development of a…
Digital Twin (DT) technology has become rather popular in recent years, promising to optimize production processes, manage the operation of cyber-physical systems, with an impact spanning across multiple application domains (e.g.,…
In this work, we consider a mobile edge computing system with both ultra-reliable and low-latency communications services and delay tolerant services. We aim to minimize the normalized energy consumption, defined as the energy consumption…
Power systems are inherently multi-timescale systems, with different physical phenomena and decision-making processes spanning multiple timescales, time horizons, and geographic scopes. I envision power systems digital twins (DTs) as…
The emergence of beyond 5G (B5G) and 6G networks underscores the critical role of advanced computer-aided tools, such as network digital twins (DTs), in fostering autonomous networks and ubiquitous intelligence. Existing solutions in the DT…
Mobile edge computing has become an effective and fundamental paradigm for futuristic autonomous vehicles to offload computing tasks. However, due to the high mobility of vehicles, the dynamics of the wireless conditions, and the…
Digital twin (DT) is the recurrent and common feature in discussions about future technologies, bringing together advanced communication, computation, and artificial intelligence, to name a few. In the context of Industry 4.0, industries…
Fully harvesting the gain of multiple-input and multiple-output (MIMO) requires accurate channel information. However, conventional channel acquisition methods mainly rely on pilot training signals, resulting in significant training…
Vehicle Twins (VTs) as digital representations of vehicles can provide users with immersive experiences in vehicular metaverse applications, e.g., Augmented Reality (AR) navigation and embodied intelligence. VT migration is an effective way…
Decentralised online learning enables runtime adaptation in cyber-physical multi-agent systems, but when operating conditions change, learned policies often require substantial trial-and-error interaction before recovering performance. To…
Metaverse and Digital Twin (DT) have attracted much academic and industrial attraction to approach the future digital world. This paper introduces the advantages of deep reinforcement learning (DRL) in assisting Metaverse system-based…
Digital Twins are being used as an enabling technology in 6G applications across various domains, valued for their data-driven insights and real-time decision-making capabilities. However, integrating Digital Twins into 6G environments…