Periodic Reporting for period 1 - INSTINCT (Joint Sensing and Communications for Future Interactive, Immersive, and Intelligent Connectivity Beyond Communications)
Reporting period: 2024-01-01 to 2025-06-30
The INSTINCT project is aimed to enable sustainable, interactive, immersive, and intelligent ‘beyond communications’ sixth generation (6G) connectivity with 13 partners from 5 different European countries. The project wants to achieve the development of three complementary but critical breakthrough technology pillars during its three-years duration:
• sensing-assisted communication technologies, thus allowing localization, tracking, mapping, monitoring, imaging, incident detection and semantics become integral parts of connectivity services (Pillar 1),
• intelligent surfaces, holographic radios and cell free systems, which offer wavefront engineering functionalities and tuneability of the wireless environment and can act as reconfigurable and intelligent sensors (Pillar 2), and
• Machine Learning techniques-based co-design of Sensing and Communications (Pillar 3).
These pillars will result in three demonstrators – two hardware and one software demonstrations for interactive, immersive and intelligent connectivity in 6G usage scenarios.
The three objectives are summarized below.
Objective 1: Enhancing Connectivity Through Integrated Sensing and Communication
This objective focuses on merging communication and sensing technologies to enable more responsive and intelligent network services. By leveraging various frequency bands and advanced signal processing, the aim is to support emerging applications in future 6G networks.
Purpose: To develop systems that can simultaneously communicate and sense their environment, improving location accuracy, situational awareness, and overall network efficiency.
Approach: Utilize shared infrastructure and dual-function waveforms to reduce energy and cost, while integrating artificial intelligence for adaptive resource management.
Impact: Enhanced reliability, coverage, and responsiveness in critical scenarios such as public safety and disaster recovery.
Objective 2: Building Resilient and Adaptive Networks Using Intelligent Surfaces
This objective aims to create robust and flexible connectivity solutions by incorporating reconfigurable intelligent surfaces (RIS), large intelligent surfaces (LIS), and distributed network technologies.
Purpose: To ensure consistent and high-quality connectivity even in challenging environments, such as areas with signal blockage or high user density.
Approach: Develop realistic models and optimization frameworks for smart surfaces that can sense and adapt to their surroundings, supported by advanced signal processing and system-level simulations.
Impact: Improved energy efficiency, reduced latency, and greater network availability, with a focus on scalability and sustainability.
Objective 3: Co-Designing Intelligent Networks Through AI and Advanced Hardware
This objective addresses the joint design of communication and sensing systems using artificial intelligence, machine learning, and specialized hardware solutions to support future 6G radio access networks.
Purpose: To enable intelligent, multifunctional networks capable of learning and adapting to dynamic conditions and user needs.
Approach: Employ AI-driven optimization techniques, structured learning methods, and co-designed hardware architectures to manage complexity and enhance performance.
Impact: Increased connection density, reliability, and energy efficiency, with a strong emphasis on trustworthiness and intelligent resource allocation.
• sensing-assisted communication technologies, thus allowing localization, tracking, mapping, monitoring, imaging, incident detection and semantics become integral parts of connectivity services (Pillar 1),
• intelligent surfaces, holographic radios and cell free systems, which offer wavefront engineering functionalities and tuneability of the wireless environment and can act as reconfigurable and intelligent sensors (Pillar 2), and
• Machine Learning techniques-based co-design of Sensing and Communications (Pillar 3).
These pillars will result in three demonstrators – two hardware and one software demonstrations for interactive, immersive and intelligent connectivity in 6G usage scenarios.
The three objectives are summarized below.
Objective 1: Enhancing Connectivity Through Integrated Sensing and Communication
This objective focuses on merging communication and sensing technologies to enable more responsive and intelligent network services. By leveraging various frequency bands and advanced signal processing, the aim is to support emerging applications in future 6G networks.
Purpose: To develop systems that can simultaneously communicate and sense their environment, improving location accuracy, situational awareness, and overall network efficiency.
Approach: Utilize shared infrastructure and dual-function waveforms to reduce energy and cost, while integrating artificial intelligence for adaptive resource management.
Impact: Enhanced reliability, coverage, and responsiveness in critical scenarios such as public safety and disaster recovery.
Objective 2: Building Resilient and Adaptive Networks Using Intelligent Surfaces
This objective aims to create robust and flexible connectivity solutions by incorporating reconfigurable intelligent surfaces (RIS), large intelligent surfaces (LIS), and distributed network technologies.
Purpose: To ensure consistent and high-quality connectivity even in challenging environments, such as areas with signal blockage or high user density.
Approach: Develop realistic models and optimization frameworks for smart surfaces that can sense and adapt to their surroundings, supported by advanced signal processing and system-level simulations.
Impact: Improved energy efficiency, reduced latency, and greater network availability, with a focus on scalability and sustainability.
Objective 3: Co-Designing Intelligent Networks Through AI and Advanced Hardware
This objective addresses the joint design of communication and sensing systems using artificial intelligence, machine learning, and specialized hardware solutions to support future 6G radio access networks.
Purpose: To enable intelligent, multifunctional networks capable of learning and adapting to dynamic conditions and user needs.
Approach: Employ AI-driven optimization techniques, structured learning methods, and co-designed hardware architectures to manage complexity and enhance performance.
Impact: Increased connection density, reliability, and energy efficiency, with a strong emphasis on trustworthiness and intelligent resource allocation.
During the first 18 months, the project made progress in all six expected outcomes :
1. Develop wireless systems that are super fast, reliable, and accurate, while using less energy and working across different frequency ranges.
2. Create new network designs that can handle multiple tasks at once, like storing data locally and sensing the environment.
3. Build technologies that reduce energy use and limit exposure to radio signals, while improving how devices connect without relying on fixed cell towers.
4. Use smart AI systems to help networks adjust and improve themselves automatically for better performance.
5. Enable new types of wireless applications by combining communication with sensing capabilities.
6. Design solutions that make networks more eco-friendly and visually unobtrusive in urban areas.
1. Develop wireless systems that are super fast, reliable, and accurate, while using less energy and working across different frequency ranges.
2. Create new network designs that can handle multiple tasks at once, like storing data locally and sensing the environment.
3. Build technologies that reduce energy use and limit exposure to radio signals, while improving how devices connect without relying on fixed cell towers.
4. Use smart AI systems to help networks adjust and improve themselves automatically for better performance.
5. Enable new types of wireless applications by combining communication with sensing capabilities.
6. Design solutions that make networks more eco-friendly and visually unobtrusive in urban areas.
The project has contributed effectively beyond state of the art. This is reflected in more than 50 dissemination activities (talks, workshops, demonstrations), 40 publications and 9 standardization activities. In EuCNC 2025 alone, INSTINCT partners contributed to 5 workshops, several special sessions and papers along with a booth with multiple hardware and software demonstrators.