SCOPE:

The 13th International Conference on Wireless Networks and Mobile Communications (WINCOM 2026) will be held from October 21 to 24, 2026, in Tangier, Morocco. WINCOM has established itself as an important international forum for the exchange of innovative ideas, in-depth technical discussions, and the dissemination of cutting-edge research among researchers, practitioners, and industry experts actively involved in the fields of wireless and mobile communications.

As the flagship conference of the MobiTic Association, WINCOM 2026 will be thematically centered on “AI-Driven Wireless Systems”, highlighting the transformative role of Artificial Intelligence (AI) and Machine Learning (ML) in the design, optimization, and management of next-generation wireless and mobile networks. The conference will focus on intelligent radio resource management, AI-based network optimization, self-organizing and autonomous networks, edge intelligence, and AI-enabled 5G and 6G systems, reflecting the evolution of communication infrastructures toward adaptive, autonomous, and data-driven network architectures.

The conference is officially ranked CORE C in the CORE Conference Ranking 2026, underscoring its growing international recognition and its commitment to high scientific quality, rigorous peer review, and strong organizational standards.

All accepted and presented papers at WINCOM 2026 will undergo a rigorous peer-review process and will be submitted for publication in IEEE Xplore, ensuring wide dissemination within the global research community. The conference proceedings will also be submitted for indexing in major international databases, including Scopus, Web of Science (ISI), DBLP, and other leading indexing services.

Papers of outstanding quality and originality will be invited to submit extended versions for potential inclusion in special issues of selected international journals. Discussions are currently ongoing with several renowned international journals to finalize special issue opportunities associated with WINCOM 2026.

Topics of Interest:

WINCOM 2026 solicits high-quality and original research contributions in wireless and mobile networking, including (but not limited to) the following tracks:

Track 1: Wireless and Mobile Communications

    Wireless and Mobile Networks
    Future Internet and Next-Generation Networking
    Green and Sustainable Communication Systems
    Risk-Aware and Resilient Wireless Networks
    Modeling and Performance Evaluation of SDN, NFV, and Network Slicing
    Satellite Communications and Non-Terrestrial Networks (NTN)
    Millimeter-Wave and Terahertz Communications
    Massive MIMO and Multi-User MIMO Systems
    Localization, Positioning, and Mapping
    Cross-Layer Design and Optimization (PHY–MAC–Network Layers)
    Multi-Hop Communications: Ad Hoc, WSN, DTN, VANET
    Vehicular and Intelligent Transportation Networks
    Implementation, Testbeds, and Experimental Prototypes
    6G Network Programmability and Softwarization
    Sub-Networking and Micro-Networks for 6G
    Semantic Communications and Goal-Oriented Networking
    Routing, QoS/QoE, and Risk-Aware Traffic Engineering
    Optical, Quantum, and Hybrid Communication Networks
    Communication Theory and Information Theory
    Cognitive and Self-Adaptive Networking
    Intelligent Reflecting Surfaces (IRS) and Closed-Loop Cognitive Systems
    Radio Resource Management, Allocation, and Scheduling
    Channel Modeling, Capacity Estimation, and Equalization
    Advanced Signal Processing for Wireless Communications 

Track 2: Security, Privacy, and Cybersecurity

    Security and Cybersecurity in Wireless and Mobile Networks
    Risk-Aware Security and Threat Modeling for 5G/6G Networks
    Trust, Privacy, and Blockchain-Based Platforms
    Cybersecurity Challenges in 6G Networks
    Secure xApps and rApps for Programmable Networks
    Attacks, Threats, and Vulnerability Analysis in 6G
    Security of Foundational Models and Large-Scale AI Models
    Secure and Privacy-Preserving Machine Learning
    ML-Based Device and Traffic Fingerprinting
    Energy and Cost-Aware Security Mechanisms
    Coding and Information-Theoretic Security
    Privacy Preservation at the Edge and in Distributed Systems
    Differential Privacy and Secure Aggregation
    Secure Over-the-Air Updates and Software Supply Chains
    Security for Big Data and Distributed AI Systems
    Resilient and Trustworthy AI for Communication Networks 

Track 3: IoT, Smart Cities, and New Applications

    Internet of Things (IoT) Architectures and Applications
    IoT for Smart Cities and Smart Infrastructures
    Risk-Aware IoT Systems and Critical Infrastructure Protection
    Digital Twins for Communication Networks and Smart Systems
    QoS/QoE in Next-Generation Networks
    Ultra-Low-Power IoT Technologies and Embedded Architectures
    Cloud, Edge, and Fog Computing for IoT
    Intelligent Vehicles and Vehicular Communications
    Autonomous Driving and Cooperative Perception
    Industry 5.0 and Cyber-Physical Systems
    Robotics Communications and Networked Control Systems
    Co-Design of Communication, Control, and Computing
    Mobility Management and Service Continuity
    M2M and Massive Machine-Type Communications (mMTC)
    XR (VR/AR/MR) and Metaverse Networking
    Multimedia Streaming and Immersive Services 

Track 4: ML & AI in Communications network

    Machine Learning and Artificial Intelligence for Communication Networks
    AI-Native and AI-Driven Network Architectures
    Semantic Learning and Semantic Communications for Networks
    Semantic Federated Learning and Knowledge-Oriented Aggregation
    Large Language Models (LLMs) for Network Management and Automation
    Foundational Models for Telecom and Networking
    Reinforcement Learning for Resource Allocation and Control
    Open Radio Access Networks (O-RAN) and Open Networking
    RAN Intelligent Controllers (RIC), xApps, and rApps
    Deep Learning for Emerging Network Applications
    Secure, Robust, and Risk-Aware Learning Methods
    Resilient and Trustworthy AI Systems
    Contrastive, Transfer, and Continual Learning
    Edge Intelligence and On-Device Learning
    Federated Learning and Distributed Intelligence
    Model-Mediated and Knowledge-Centric Learning
    AI for Edge, Fog, and Cloud Computing