Mathematical Methods for AI-Enhanced Wireless Communications in Smart Cities
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E2: Control Theory and Mechanics".
Deadline for manuscript submissions: 20 December 2025 | Viewed by 39
Special Issue Editor
Interests: Internet of Things; intelligent reflective surface; graph neural network; machine learning for wireless communication; metaverse applications; visible-light communication
Special Issue Information
Dear Colleagues,
The rapid growth of smart cities is driving the demand for intelligent, adaptive, and scalable wireless communication systems. This Special Issue aims to highlight recent advances in AI-driven technologies that optimize wireless networks in urban environments. The increasing complexity of smart cities has created a critical demand for intelligent, adaptive, and efficient wireless communication systems capable of handling massive connectivity, dynamic data flows, and real-time responsiveness. Artificial intelligence (AI), particularly machine learning, deep learning, and graph-based models, has emerged as a powerful enabler for optimizing wireless networks in these highly dynamic environments.
This Special Issue aims to bring together cutting-edge research that integrates mathematical modelling, optimization theory, stochastic processes, graph theory, and machine learning algorithms for the design, analysis, and implementation of AI-driven wireless communication systems in smart cities.
We seek high-quality original research and review papers that achieve the following:
- Develop novel mathematical frameworks to model, analyze, and optimize wireless networks empowered by AI technologies.
- Propose new algorithms for resource allocation, channel estimation, mobility management, and network scalability using rigorous mathematical formulations.
- Utilize graph neural networks (GNNs), game theory, control theory, and geometric deep learning to enhance performance, adaptability, and intelligence in urban communication infrastructures.
- Explore applications of intelligent reflecting surfaces (IRS), federated learning, and edge AI within the context of urban environments, backed by solid mathematical foundations.
By combining theory and practical relevance, this Special Issue will serve as a platform for interdisciplinary collaboration between researchers in mathematics, computer science, electrical engineering, and urban informatics.
Dr. Mohammad Abrar Shakil Sejan
Guest Editor
Manuscript Submission Information
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Keywords
- AI-based communication network design
- wireless communication network
- sensor network
- AI-enabled 6G and beyond wireless communication
- federated learning and edge AI in smart cities
- intelligent reflective surfaces (IRS) for urban wireless network
- graph neural networks in urban IoT systems
- AI for spectrum management and resource allocation
- machine learning for vehicular and drone communications
- real-time wireless communication analytics using AI
- secure and privacy-preserving AI in wireless networks
- applications of AI-driven networks in traffic, energy, and public safety
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