AI-Enabled Signal Processing for Space–Air–Ground Integrated Networks

Dear Colleagues,

In the modern landscape of communication systems, the integration of satellites, aerospace vehicles, aircraft, and ground cellular networks, namely Space–Air–Ground Integrated Networks (SAGINs), presents unparalleled opportunities alongside unique challenges. SAGINs signify a paradigm shift in the telecommunications sector, offering seamless connectivity and ubiquitous coverage across diverse terrains and altitudes. However, the effective operation of such networks necessitates complex signal processing solutions that are capable of adapting to rapidly changing environmental conditions, mobility patterns, and user demands. Artificial intelligence (AI)-enabled signal processing holds transformative potential, providing unprecedented capabilities in real-time data analysis, adaptive resource allocation, and intelligent decision making. Traditional signal processing algorithms often falter in scenarios characterized by rapid mobility, frequent handovers, and unpredictable channel conditions, posing significant obstacles to reliable communication. However, through the integration of AI, innovative solutions can be designed to not only mitigate the impact of dynamic environments but also leverage them to enhance network efficiency and resilience. This Special Issue aims to explore the profound intersection of AI and signal processing within SAGINs, with a primary focus on enhancing network performance and overcoming the inherent challenges posed by the high dynamics of aircraft and satellites.

Topics of interest include but are not limited to the following:

• Adaptive signal processing techniques for dynamic environments;
• Dynamic detection of aircraft and satellites in SAGINs;
• Resource allocation for SAGINs using AI algorithms;
• Machine learning for SAGIN optimization;
• Security and privacy enhancement in SAGINs;
• Adaptive beamforming and MIMO techniques for SAGINs;
• Edge computing in SAGINs;
• Adaptive routing algorithms for SAGINs.

Dr. Xin Liu
Guest Editor

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• Space–Air–Ground networks
• signal processing
• SAGIN