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KAUST Mathematical Model Tackles 5G Interference With Aircraft
The simulations showed that one tower inside the exclusion zone could reduce 5G efficiency by 20%, and up to 50% with three towers.
As 5G networks expand worldwide, concerns over aviation safety have sharpened. At the center is the risk that 5G signals may interfere with aircraft radio altimeters — instruments critical for determining altitude during landings and in low-visibility conditions. A research team at King Abdullah University of Science and Technology (KAUST) has now come up with a mathematical model to prevent such conflicts, aiming to protect aviation systems while preserving strong network performance.
The study, published in IEEE Transactions on Wireless Communications, introduces the idea of an ideal exclusion zone. These zones define areas near airports where higher-frequency 5G signals should be restricted to reduce interference. The approach offers regulators a framework for balancing passenger safety with mobile connectivity demands.
Led by Professor Mohamed-Slim Alouini, the KAUST team is the first to use stochastic geometry — a mathematical tool for modelling random network layouts — to forecast how 5G transmissions might overlap with radio altimeter signals. “5G operates near the same bandwidth as aircraft radio altimeters, which may cause signal interference,” explained Alouini. “This highlights the need to establish exclusion zones to reduce interference levels”.
The research suggests that triangular-shaped exclusion zones provide the best compromise, offering effective shielding for altimeters while limiting the impact on mobile networks. Within these areas, regulators could allow only lower-frequency signals, keeping higher-frequency bands that are more prone to interference outside the zone.
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Simulation results underscored the stakes. A single 5G tower placed inside the exclusion zone was shown to reduce overall efficiency by 20%, while three towers could slash performance by as much as 50%.
The project, supported by Saudi Arabia’s Communications, Space & Technology Commission (CST), positions the Kingdom at the forefront of a global debate. As countries refine their 5G rollout strategies, KAUST’s framework could help regulators worldwide protect aviation safety without stalling digital infrastructure progress.
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OpenAI’s ChatGPT Health Is A Private Space For Health Data
A new health mode lets the popular AI platform tap medical records and fitness apps while walling off sensitive information.
OpenAI has created ChatGPT Health, a separate space inside its chatbot platform for handling medical and wellness data. The opt-in feature starts with a small US cohort before widening out.
Health-related questions have long driven traffic to AI tools. OpenAI says over 230 million people ask ChatGPT about health or insurance each week. The new mode adds personal context to that behavior but stops short of diagnosis or treatment advice.
Users can connect records from participating US providers through b.well and link apps such as Apple Health, MyFitnessPal, Function and Weight Watchers. Some links are US-only, while Apple Health needs iOS. Once connected, ChatGPT can surface patterns in labs, summarize information ahead of a clinic visit or help map diet and exercise choices against past data.
The data sits apart from other chat information. Health has its own memories and does not spill into other conversations. Users can view or delete health memories at any time. OpenAI says this material is not used to train its models.
Security is much heavier in this section too. Health adds isolation and purpose-built encryption on top of the platform’s baseline protections. App connections require explicit permission, and disconnecting cuts the feed immediately.
“ChatGPT Health is another step toward turning ChatGPT into a personal super-assistant that can support you with information and tools to achieve your goals across any part of your life,” wrote Fidji Simo, OpenAI’s applications chief.
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Physicians had input during development, though OpenAI has not detailed how that shaped the end product. The launch follows Health Bench, a dataset released in May to test models on realistic medical cases.
While currently rooted in the US healthcare ecosystem, the approach may draw interest in the Gulf and wider MENA markets as governments push digital health records and patient portals under modernization programs. Adoption will depend on whether users trust an AI assistant with such personal material and whether it fits clinical routines.
For OpenAI, the move marks a cautious step into regulated terrain and signals a shift toward sector-specific uses of generative AI.
