CALL FOR PAPERS

Special Session: AI-Native and Data-Driven Management for Next-Generation Networks

Part of the 2026 IEEE International Symposium on Measurement in Networking and Communications

Napoli, Italy – July 13-16, 2026

https://mnc2026.ieee-ims.org/program/special-sessions#session-1-1

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We invite the submission of original research contributions to the Special Session on AI-Native and Data-Driven Management for Next-Generation Networks, organized within the framework of the 2026 IEEE International Symposium on Measurement in Networking and Communications, held in Napoli, Italy, July 13–16, 2026.

AI-Native and Data-Driven Management is important and promising for Measurement in Networking since it will enable automatic optimization and network management. Over the years, Artificial Intelligence (AI) and Machine Learning (ML) have become increasingly pervasive in networking and communications, playing a key role in the development, deployment, and management of next-generation networks. Current research trends show how AI can enhance 5G networks at at the RAN, Edge, and Core layers, using measured data coming from multiple entities.

While AI adoption in 5G has been an evolving process, 6G is envisioned as truly AI-native. The next generation of mobile networks will embed “connected intelligence” throughout its architecture, leveraging AI for network design, optimization, and autonomous operation. In 6G, AI will not only enhance network performance but also enable and support AI-driven services running seamlessly across the entire network from the user equipment to the network core. Through this AI-native framework, the network will be capable of analyzing real-time data to jointly orchestrate functions such as scheduling, network slicing, and strategic planning.

AI technologies in fact, expand new potential in the optimization of the full end-to-end chain of the physical layer, from the transmitter to the receiver, enabling self-optimization by combining advanced sensing and data collection also introducing the capability to consider network metrics, such as current spectrum, power conditions, and number of connections, evolving because of signal reflections off buildings and weather patterns for constant re-optimization.

Monitoring of real-time environmental and contextual data is a promising enabler for ML-based air interface optimization, leading to more efficient spectrum use and reduced latency.

Not only, nowadays, AI is now further enhanced and made more interpretable through XAI methodologies, which allow us to better understand how the algorithms operate and which features are most relevant for predictions.

Topics of interest include, but are not limited to:

•    Measurements for 6G, beyond-5G, and next-generation communications

•    Trustworthy AI and explainable measurement approaches

•    AI/ML-driven network measurement and diagnostics

•    Software-defined and virtualized network measurement

•    Big Data analytics for network traffic, QoS, and QoE evaluation

•    Security, privacy, and reliability network measurements in 5G and 6G

***Timeline***

Paper registration:    April 6, 2026

Initial manuscript deadline:    April 6, 2026

***Manuscript submission information***

Authors are invited to submit a Full Paper (4-6 pages) reporting original research of a theoretical or applied nature using the online submission system, EDAS.

EDAS Submission Link: https://edas.info/N34568

Further information available: https://mnc2026.ieee-ims.org/author-information

***Special Session Chairs***

Prof. Giovanni Stanco

University of Naples Federico II, Italy

Email: giovanni.stanco@unina.it

Prof. Stefania Zinno

University of Naples Federico II, Italy

Email: stefania.zinno@unina.it