AI-Enabled Techniques for Next-Generation Wireless Networks

Dear Colleagues,

The proliferation of wireless communication has led to a dramatic surge in data traffic, presenting considerable challenges for current network infrastructures. Traditional approaches struggle to efficiently manage resources and adapt to dynamic conditions, necessitating innovative solutions. Integrating artificial intelligence (AI) into next-generation wireless network strategies presents promising avenues for addressing these challenges. AI enables intelligent decision making, resource optimization, and adaptive management, thereby enhancing network performance, reliability, and scalability. This approach aligns well with the growing demand for seamless connectivity, higher data rates, and diverse services in increasingly complex wireless environments.

“AI for Next-Generation Wireless Networks” actively employs AI methods to significantly enhance the performance, efficiency, and resource utilization of wireless communication technologies. This field encompasses a broad spectrum of research and development efforts aimed at integrating AI techniques into various facets of wireless networks, including but not limited to the following:

• AI-based resource allocation and optimization for next-generation wireless networks;
• AI-based network management for next-generation wireless networks;
• Intelligent radio access to improve the efficiency and adaptability of wireless networks;
• Utilizing AI-powered analytics for predictive maintenance and fault detection in wireless networks;
• AI-driven methods to enhance Quality of Service (QoS) for wireless networks;
• Leveraging AI for security enhancement of wireless networks;
• Exploring AI techniques for spectrum management and cognitive radio in wireless communication;
• Using AI algorithms to optimize network slicing and virtualization, enabling flexible network configurations tailored to diverse service requirements;
• AI-driven techniques to optimize communication links between Unmanned Aerial Vehicles (UAVs) and ground base stations;
• UAV-assisted communication with intelligent surface for air-to-ground integrated communication;
• Context-aware services by integrating IoT data with AI algorithms;
• Integrating IoT data and AI algorithms enhances vehicle-to-everything (V2X) communication;
• Autonomous vehicles equipped with AI algorithms for wireless networks;
• AI-enabled Information sensing integration for wireless networks;
• Semantic AI and Generative Models for wireless networks.

Dr. Ishtiaq Ahmad
Guest Editor

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• AI
• wireless networks
• wireless communication