Multi-Object Tracking for Collision Avoidance Using Multiple Cameras in Open RAN Networks

This paper deals with the multi-object detection and tracking problem, within the scope of open Radio Access Network (RAN), for collision avoidance in vehicular scenarios. To this end, a set of distributed intelligent agents collocated with cameras are considered. The fusion of detected objects is done at an edge service, considering Open RAN connectivity. Then, the edge service predicts the objects trajectories for collision avoidance. Compared to the related work a more realistic Open RAN network is implemented and multiple cameras are used.

Enabling Continuous 5G Connectivity in Aircraft through Low Earth Orbit Satellites

As air travel demand increases, uninterrupted high-speed internet access becomes essential. However, current satellite-based systems face latency and connectivity challenges. While prior research has focused on terrestrial 5G and geostationary satellites, there is a gap in optimizing Low Earth Orbit (LEO)-based 5G systems for aircraft. This study evaluates the feasibility of deployment strategies and improving signal quality with LEO satellites for seamless in-flight 5G connectivity. Using Matlab and Simulink, we model satellite trajectories, aircraft movement, and handover mechanisms, complemented by ray-tracing techniques for in-cabin signal analysis. Results show that proposed LEO satellite configurations enhance coverage and reduce latency, with sequential handovers minimizing service interruptions. These findings contribute to advancing in-flight 5G networks, improving passenger experience, and supporting real-time global connectivity solutions.

AI-Driven Tactical Communications and Networking for Defense: A Survey and Emerging Trends

The integration of Artificial Intelligence (AI) in military communications and networking is reshaping modern defense strategies, enhancing secure data exchange, real-time situational awareness, and autonomous decision-making. This survey explores how AI-driven technologies improve tactical communication networks, radar-based data transmission, UAV-assisted relay systems, and electronic warfare resilience. The study highlights AI applications in adaptive signal processing, multi-agent coordination for network optimization, radar-assisted target tracking, and AI-driven electronic countermeasures. Our work introduces a novel three-criteria evaluation methodology. It systematically assesses AI applications based on general system objectives, communications constraints in the military domain, and critical tactical environmental factors. We analyze key AI techniques for different types of learning applied to multi-domain network interoperability and distributed data information fusion in military operations. We also address challenges such as adversarial AI threats, the real-time adaptability of autonomous communication networks, and the limitations of current AI models under battlefield conditions. Finally, we discuss emerging trends in self-healing networks, AI-augmented decision support systems, and intelligent spectrum allocation. We provide a structured roadmap for future AI-driven defense communications and networking research.

Enhancing 5G O-RAN Communication Efficiency Through AI-Based Latency Forecasting

The increasing complexity and dynamic nature of 5G open radio access networks (O-RAN) pose significant challenges to maintaining low latency, high throughput, and resource efficiency. While existing methods leverage machine learning for latency prediction and resource management, they often lack real-world scalability and hardware validation. This paper addresses these limitations by presenting an artificial intelligence-driven latency forecasting system integrated into a functional O-RAN prototype. The system uses a bidirectional long short-term memory model to predict latency in real time within a scalable, open-source framework built with FlexRIC. Experimental results demonstrate the model's efficacy, achieving a loss metric below 0.04, thus validating its applicability in dynamic 5G environments.