WINCOM 2026 (International Conference on Wireless Networks and Mobile Communications) is an academic conference held in Tangier, Morocco on 2026-10-21. The paper submission deadline is 2026-05-31. Acceptance notifications are sent on 2026-08-05.
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