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Special Issue: Call for Papers

Please find the the deatils about this Speciall Issue on AI-native Smart Radio Environments for 6G within the IEEE Internet of Things Journal with Dr. Maged Elkashlan as Guest Editor.

Important Dates:

Submission Deadline: December 31, 2026

First Review Due: February 15, 2027

Revision Due: March 15, 2027

Second Reviews Due/Notification: April 30, 2027

Scope

Fluid Antenna Systems (FAS) are emerging as a key technology for next-generation IoT networks by enabling dynamic adaptation of antenna positions, activation patterns, and radiation characteristics in real time. Unlike conventional fixed antennas, FAS can continuously reconfigure themselves to optimize connectivity, reliability, and spectrum utilization across diverse applications such as smart cities, Industry 4.0, precision agriculture, and intelligent healthcare.

The integration of artificial intelligence further enhances FAS capabilities. Agentic AI can autonomously monitor wireless environments and optimize antenna configurations, while Edge AI enables real-time, distributed decision-making directly at IoT devices. Large Language Models (LLMs) can provide intuitive interfaces for network management and support semantic communication paradigms. Together, these technologies enable self-optimizing, self-healing, and adaptive IoT ecosystems.

This Special Issue focuses on the convergence of FAS and AI for autonomous IoT networks. It seeks contributions on FAS design and optimization, AI-driven antenna control, distributed edge intelligence, LLM-enabled network management, and practical implementations demonstrating the benefits of AI-empowered FAS across a wide range of IoT applications.

Topics of interest include (but are not limited to):

· FAS system design and optimization for intelligent IoT ecosystems

· Agentic AI systems for autonomous FAS control and optimization

· Edge AI for distributed and real-time FAS adaptation

· LLM-powered natural language interfaces for FAS configuration

· Fluid antenna multiple access (FAMA) with AI-enhanced scheduling

· Deep learning and reinforcement learning for FAS optimization

· Multi-agent coordination for distributed FAS-IoT networks

· Generative AI for FAS channel modeling and beamforming design

· FAS-enabled integrated sensing and communication (ISAC) systems

· Semantic communication enabled by LLMs and FAS integration

· Self-evolving FAS networks with continuous learning capabilities

· Explainable AI for interpretable FAS decision-making

· Energy-efficient AI-FAS co-design for sustainable IoT

· FAS for massive machine-type communications and ultra-reliable IoT

· Smart city applications with AI-empowered FAS infrastructure

· Industrial IoT and smart manufacturing with FAS connectivity

· Healthcare IoT with FAS-enabled reliable communications

· Autonomous vehicle networks with FAS coordination

· FAS for precision agriculture and environmental monitoring

· Experimental platforms and testbeds for AI-FAS integration

· Standardization and commercialization of FAS for IoT systems

· Security and privacy mechanisms for AI-empowered FAS networks.

Submission:

The original manuscripts to be submitted need to follow the guidelines at: ieee-iotj.org/wp-content/uploads/2025/02/IEEE-IoTJ-Author..., which should not be concurrently submitted for publication in other venues. Authors should submit their manuscripts through the IEEE Author Portal at: ieee.atyponrex.com/journal/iot. The authors must select as "Special Issue on Fluid Antenna Systems for Autonomous IoT: Agentic AI, Edge Intelligence, and Foundation Models" when they reach the "Article Type" step in the submission process.