Call for Papers

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The integration of digital twins (DTs) into wireless systems has traditionally focused on modeling and analyzing the behavior of wireless networks themselves, building on the foundational role of DTs in industrial and cyber-physical domains. In this vision, wireless networks are treated as the object to be twinned, enabling enhanced monitoring, diagnostics, and pre-deployment planning. This special issue introduces a paradigm shift: positioning wireless networks not as the subject of DT modeling, but as an adaptive substrate that enables scalable, application-aware, closed-loop Digital Twin Networks (DTNs). In this new vision, DTNs span across the physical and digital worlds and are tightly coupled with the wireless infrastructure to support real-time decision-making, control, and feedback in complex environments. From robotic systems in agriculture to autonomous vehicles and immersive AR/VR applications, DTNs act not merely as digital representations but as intelligent agents that dynamically reconfigure wireless resources in response to evolving application requirements, sensor inputs, and environmental conditions. This proposal emphasizes closed-loop optimization as a core architectural element of next-generation DTNs. Beyond static mirroring, DTs in our framework operate as active participants in the network control loop—interacting with heterogeneous edge-cloud resources, continuously adapting task scheduling, data flows, and wireless parameters to serve specific semantic or mission-critical goals. This creates new technical frontiers in semantic-aware data abstraction, cross-domain synchronization, and distributed twin orchestration. While significant research has explored the use of DTs to monitor and enhance wireless infrastructure, critical challenges remain in enabling DT-driven network reconfiguration, real-time cross-layer feedback between DTs and wireless stacks, and application-specific twin formation and evolution. These challenges demand new optimization principles, learning-based control mechanisms, and trustworthy data collection frameworks.

This special issue seeks to gather cutting-edge contributions addressing the co-design of DTs and reconfigurable wireless systems, with a focus on scalable DT deployment, real-time semantic control, and interdisciplinary applications. We welcome original research across the following topics (but not limited to): 

Closed-Loop Optimization

• Twin-in-the-loop architectures for real-time feedback and control
• Cross-layer optimization frameworks for DT-guided wireless adaptation
• Reinforcement learning and differentiable control for self-optimizing DTNs
• Predictive DT analytics for proactive fault detection and resilience
• Edge–cloud coordination for distributed closed-loop orchestration
• Convergence and stability analysis for feedback-driven DTNs
• Energy-efficient and latency-bounded DT synchronization mechanisms
• Security, privacy, and robustness in real-time twin control loops 

Application-Aware Design

• Wireless-native architectures supporting semantic and task-aware DTs
• Dynamic creation, migration, and evolution of DTs across wireless domains
• AI-native and foundation model-based DT intelligence for context understanding
• Federated and hierarchical management of heterogeneous DT ecosystems
• Open interfaces and intent-based APIs linking DTs with radio access network controllers
• DT-driven semantic service provisioning and adaptive edge scheduling
• DT-enabled use cases in autonomous systems, agriculture, and/or immersive XR
• Standardization and interoperability for application-centric DTNs

Submission Guidelines

Prospective authors should submit their manuscripts following the IEEE JSAC guidelines. Authors should submit a PDF version of their complete manuscript through Scholar One Manuscripts (authors should have an account on the platform).

Important Dates

Manuscript submission: 1 May 2026
First round of review results notification: 15 July 2026
Final acceptance notification: 1 September 2026
Final manuscript due: 15 September 2026
Planned Publication: Fourth Quarter 2026

Guest Editors

Yuchen Liu (Lead Guest Editor)
North Carolina State University, USA

Tommaso Melodia
Northeastern University, USA 

Xingqin Lin
NVIDIA, USA

Mingzhe Chen
University of Miami, USA

Berk Canberk
Edinburgh Napier University, UK

Sara Garcia Sanchez
IBM, USA