AI-Enabled Mobile, Edge, and Networked Systems

Dear Colleagues, 

The proliferation of 5G-Advanced and emerging 6G wireless technologies, coupled with the exponential growth of intelligent mobile devices, Internet of Things (IoT) terminals, and bandwidth-intensive/ultra-low-latency applications, has imposed unprecedented challenges on current mobile, edge, and networked systems. Traditional network architectures and system designs, which follow a hardware-defined, protocol-centric, and manually optimized paradigm, struggle to address the dynamic heterogeneity of network environments, the explosive growth of data traffic, and the stringent requirements of emerging artificial intelligence (AI) applications (e.g., on-device large language models (LLMs), multi-modal intelligent perception, autonomous driving, and the industrial Internet).

In recent years, the AI-enabled (artificial intelligence-native) design paradigm has emerged as a transformative solution for next-generation information systems. Unlike conventional "AI-on-top" approaches that retrofit AI algorithms into existing system architectures as an add-on function, AI-enabled systems embed AI capabilities into the core design of architecture, protocol stack, resource management, and security mechanisms from the ground up. This paradigm shift enables mobile, edge, and networked systems to achieve end-to-end intelligent autonomy, self-optimization, and adaptive evolution, unlocking the full potential of AI in ubiquitous wireless environments.

Despite rapid advances in related research, the field of AI-enabled mobile, edge, and networked systems still faces critical unresolved challenges: the lack of unified architectural frameworks, lightweight and efficient AI implementation for resource-constrained devices, end-to-end performance optimization across the end-edge-cloud continuum, trustworthy and secure AI-enabled system design, and the persistent gap between theoretical research and industrial deployment. This Special Issue addresses these gaps by bringing together leading academic researchers and industry practitioners to present cutting-edge advances, tackle core technical bottlenecks, and shape future research directions in this rapidly evolving field.

The primary aim of this Special Issue is to curate a high-quality collection of original research articles and comprehensive review papers that showcase the latest theoretical breakthroughs, technological innovations, system implementations, and real-world applications of AI-enabled mobile, edge, and networked systems. This Special Issue seeks to build a collaborative community for cross-domain researchers, facilitate the exchange of novel ideas and engineering best practices, and advance the standardization and commercialization of AI-enabled technologies in next-generation mobile and wireless ecosystems. We welcome submissions that address fundamental theoretical challenges, propose novel technical solutions, present validated hardware/software prototypes, or provide systematic overviews of state-of-the-art developments in the field.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

• AI-enabled architectural design for 6G/beyond-5G mobile and wireless networks;
• End–edge–cloud collaborative AI-enabled systems for mobile and IoT applications;
• AI-enabled resource orchestration, network slicing, and traffic management in edge computing environments;
• Lightweight AI model design, on-device inference optimization, and adaptive deployment for AI-enabled mobile terminals;
• AI-enabled protocol stack design and cross-layer optimization for wireless networked systems;
• Trustworthy AI-enabled systems: privacy preservation, cybersecurity, explainability, and algorithmic fairness;
• AI-enabled network automation, self-optimization, self-healing, and intent-driven networking;
• Digital twin-empowered AI-enabled edge and networked systems;
• AI-enabled integrated sensing and communication (ISAC) systems;
• Energy-efficient and sustainable AI-enabled mobile/edge systems;
• Testbeds, prototypes, and field trials of AI-enabled mobile and networked systems;
• Standardization, industrial use cases, and business models of AI-enabled network technologies.

We look forward to receiving your contributions. 

Dr. Yaoming Zhuang
Dr. Cui Wei
Dr. Hao Wu
Guest Editors

Manuscript Submission Information

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• AI-enabled systems
• mobile edge computing
• 6G wireless networks
• edge AI
• networked systems
• end-edge-cloud collaboration
• network automation
• trustworthy AI
• integrated sensing and communication