As global standards agencies plan for future networks, telecommunications research by InterDigital and Turk Telekom in Ankara has tested joint communication and sensing technology on early 6G infrastructure, using radio waves to detect human presence behind walls without relying on cameras or connected devices.
Integrating Radio Waves and Sensing Architecture in Sixth-Generation Networks
Mobile communication networks have expanded over four decades from basic voice services into high-capacity data infrastructures. While previous generations focused on speed, capacity, and latency reduction, sixth-generation network planning introduces a fundamental architectural shift by embedding sensing capabilities directly into wireless infrastructure.
Rather than acting solely as a data conduit, the network functions as an ongoing environmental sensor capable of providing centimeter-level positioning data to track objects and urban movement. The International Telecommunication Union has formally classified joint communication and sensing among six primary usage scenarios for upcoming networks. Radio waves propagating through residential spaces, offices, and urban streets normally create signal attenuation, multi-path reflections, and scattering when encountering walls, vehicles, and human bodies. Instead of treating these physical disruptions as interference, the new technical framework analyzes the reflected signals to extract spatial and structural intelligence.
Network Trials and Structural Trials in Ankara
Practical implementation moved from theory to testing when InterDigital and Turk Telekom announced a joint trial utilizing shared cellular and wireless sensing as complementary technologies on an early sixth-generation infrastructure. Conducted at the Turk Telekom Innovation Center in Ankara, the trials demonstrated reliable, near-instantaneous detection of human occupants inside buildings. The companies reported improved accuracy, greater flexibility, and fewer blind spots compared to single-network configurations.
Research across wider frequency bands—including millimeter waves, sub-terahertz frequencies, and bands exceeding 100 gigahertz—shows that network infrastructure can infer human presence, movement, and posture behind physical barriers under controlled conditions. Human movement inside a radio-saturated room continuously alters the radio channel characteristics, allowing the system to map occupancy without requiring direct optical sightlines.
Native AI Supports Autonomous Vehicles and Digital Twins
Unlike previous network generations where machine learning served as a supplementary software optimization, upcoming networks are designed with artificial intelligence as a foundational, native component. Deep learning and neural networks will re-engineer physical layers to dynamically route and schedule data according to user environments. This high-precision positioning and data synchronization supports complex automation requirements, including absolute autonomous vehicle navigation and the creation of urban digital twins that simulate smart city movements in real time with high energy efficiency.
In industrial environments, the technology aims to protect worker safety, track factory robotics, and monitor physical materials while reducing reliance on dedicated video cameras and continuous video streaming. The system can detect falls or track breathing patterns without requiring wearable devices, while offering guidance and vehicle traffic management in dense urban settings. However, removing optical cameras does not eliminate observation; sensing data still reveals physical positioning and activity without capturing traditional visual pixels.
Standardization Groups Address Privacy Risks and Data Leakage
The dual nature of the technology creates distinct security and privacy challenges. Concerns include unauthorized network use for sensing, the impossibility of securing consent from every person entering a coverage zone, and the risk of behavioral profiling, data leakage, and over-the-air radio signal tampering.
Scientific bodies and standardization groups are examining data minimization, local processing, and wave-shaping techniques to limit sensitive trait inference before commercial deployment begins.
“Integration of sensing and communications”
International Telecommunication Union, Standardization Sector
