会议信息

WINCOM 2026: International Conference on Wireless Networks and Mobile Communications

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截稿日期:
2026-05-31
通知日期:
2026-08-05
会议日期:
2026-10-21
会议地点:
Tangier, Morocco
届数:
13
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ICORE: C   浏览: 25544   关注: 2   参加: 1
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WINCOM
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会伴指数 (CP-I)

52.2 / 100
全站第 1,196 名 / 共 5,694 个会议 · 前 21%

网络与通信 第 172 / 865

学术认可 (35%)
58
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%)
71
社区关注 (10%)
24
资料公开度 (15%)
35

用到的输入: 收录等级：ICORE C · 有据可查的届次：13 · 在会伴关注它的研究者：2 人 · 过去 24 个月打开过本页的研究者：5 人

公开资料里还缺: 历年录用率 (+4.5) · 历届信息 (+3.0) · 最佳论文记录 (+2.3)
主办方认领本会议后，可直接在这一页补上；分数每晚重算。如何提升这个分数

置信度 80% —— 分数中有多大比例来自实际观测到的数据，而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.1 · 算于 2026-10-07

征稿

WINCOM 2026 (International Conference on Wireless Networks and Mobile Communications) is a ICORE C 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
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