****** First Call of papers*****
The IEEE International Conference on Machine Learning in Communications and Networking (ICMLCN 2026), Abu Dhabi, UAE
30 March - 2 April 202
Call for Papers
Workshop Title "6G Horizons: Harnessing Cutting-Edge AI Innovations for Intelligent, Sensing-Aware, and Energy-Efficient"
Summary:
6G wireless networks are envisioned to move beyond conventional data delivery and become AI-native platforms that tightly integrate communication, sensing, computing, and energy transfer. Emerging applications such as autonomous systems, extended reality, digital twins, massive machine-type communications, and large-scale distributed intelligence require ultra-low latency, extreme reliability, massive connectivity, and sustainable operation requirements that cannot be met by current network infrastructures alone. Key enabling technologies for this vision include Integrated Sensing and Communication (ISAC), Simultaneous Wireless Information and Power Transfer (SWIPT), and Reconfigurable Intelligent Surfaces (RIS). ISAC enables wireless signals to jointly support data transmission and environmental sensing, providing localization, tracking, and situational awareness. SWIPT allows networks to deliver energy and information simultaneously, supporting energy-constrained devices and sustainable operation. RIS technology introduces programmable radio environments that can dynamically shape wireless propagation, significantly improving coverage, spectral efficiency, and energy efficiency. However, the joint design and optimization of communication performance, sensing accuracy, and energy transfer in RIS-assisted ISAC–SWIPT systems is highly complex and inherently dynamic. Channel conditions, user mobility, sensing targets, and energy demands vary over time, making static or offline optimization approaches insufficient. This motivates the use of advanced AI techniques, including online learning, reinforcement learning, federated learning, and distributed intelligence. Furthermore, the integration of Agentic AI and Explainable AI (XAI) is essential to enable real-time, adaptive decision-making for critical applications such as network slicing and orchestration in future 6G networks. This workshop aims to provide a focused forum for exploring how cutting-edge AI techniques can jointly empower ISAC, SWIPT, and RIS-enabled 6G architectures, addressing both theoretical foundations and practical deployment challenges.
Workshop Webpage: https://sites.google.com/view/icmlcn2026-6gai-workshop/home
Topics of Interest:
o Multi-armed bandits for ISAC and SWIPT systems
o Safe and multi-objective online learning
o RIS-assisted communication, sensing, and power transfer
o Cascaded, mobile, and aerial RIS architectures
o Digital twins for learning-enabled wireless systems
o Communication-efficient and energy-aware learning
o Real-time analytics and 6G: Applications and Innovations.
o Edge computing and autonomous systems: Advancements and Challenges.
o Massive data processing in 6G environments.
o AI-powered network optimization in 6G networks.
o Privacy and security considerations for AI in 6G.
o Federated learning and distributed AI in 6G ecosystems.
o AI-enabled IoT and sensor networks in 6G.
o Explainable AI and transparency in 6G-enabled AI systems.
o Machine learning algorithms and models for 6G networks.
o Reinforcement learning and AI-driven decision-making in 6G scenarios.
o Standardization efforts and regulatory implications for AI in 6G.
o AI for drones, RIS, V2V, V2I, and V2X scenarios in 6G.
Submission Guidelines:
Important Dates:
Workshop Chairs: