The journey toward 6G represents the third monumental paradigm shift in mobile communications history, tracing back from 1G’s analog voice systems through 2G’s digital cellular technology, and further to 3G and 4G’s packet-switched internet capabilities. However, unlike 5G, which first flirted with AI integration via limited mechanisms such as the Network Data Analytics Function (NWDAF), 6G is conceived with AI as an equal partner to traditional communication functions. Under the guidance of the International Telecommunication Union Radiocommunication Sector (ITU-R) IMT-2030 framework, 6G systems are expected to natively implement AI-driven processes and communication paradigms, with the 3rd Generation Partnership Project (3GPP) identifying deep AI-network symbiosis as an essential requirement for 6G deployment.

This research confronts existing limitations in current network architectures, noting that prior approaches have treated AI as add-on components designed only to enhance specific network functions or analytics. Instead, the newly proposed architecture lays out a foundational integration strategy, where AI capabilities are distributed and managed across multiple network layers, enabling the network itself to act as an intelligent entity capable of self-optimization and support for AI-centric applications and services. This shift is critical to meet the rising demands for ubiquitous AI services, real-time decision-making, and automation, which characterize forthcoming technological landscapes.

The study identifies four pivotal design challenges that any 6G AI-native architecture must address. First is capability generalization, ensuring that the architecture can handle a broad spectrum of AI workloads—from low-latency, high-reliability tasks to more processing-intensive applications—with diverse performance requirements. Second, quality assurance addresses the inherently probabilistic nature of AI output, necessitating robust mechanisms to mitigate uncertainty, guaranteeing the rigorous reliability standards expected in mobile communications. Third, efficiency optimization is crucial, balancing AI’s substantial computational and energy demands with sustainable network operation. Lastly, global optimization requires an integrated approach to harmonize these competing factors, achieving an equilibrium between capability, quality, and efficiency that holistically benefits all network stakeholders.

To contend with these challenges, the researchers propose a triad of core principles guiding the architecture’s development: practicality in deployment and operation; simplicity in design to reduce complexity and overhead; and flexibility to adapt dynamically to changing demands and emerging AI technologies. Complementing these principles is a systematic, task-driven design methodology. This methodology unfolds in four rigorous steps rooted in system theory: defining clear AI-task objectives; specifying architectural elements to support these tasks; establishing hierarchical relationships for scalable deployment; and delineating connectivity frameworks to ensure seamless coordination across the network. This process is iterative, incorporating continuous refinements to optimize trade-offs among the key metrics.

The resultant 6G AI-native architecture is characterized by the integration of distributed AI components for data processing and computing, while maintaining layered centralized control to orchestrate network-wide resources and decisions. The architecture’s primary constituents include three foundational elements—connectivity, computing, and data—and three core functional modules—service, control, and execution—each fulfilling specialized roles to sustain AI-native operations. Notably, enhancements to both the core network (CN) and the radio access network (RAN) are fundamental. The CN acts as a centralized orchestrator, dynamically managing resources to foster efficient AI tasks, whereas the RAN supports distributed AI execution at the edge, critical for applications demanding ultra-low latency.

Experimental verification of this architecture was conducted using the Free5GC platform, an open-source 5G core network implementation. Testing validated the feasibility of delivering network-native AI computing services, demonstrating successful convergence of connectivity and computing management. Moreover, it showcased dynamic orchestration of AI tasks—a key capability for future 6G networks expected to handle diverse, concurrent AI workloads with varying service-level agreements (SLAs). These empirical findings underscore the architecture’s potential to meet the demanding requirements envisioned for post-5G networks.

This research also surveys the progression of 5G standardization around network-AI integration. It highlights the evolutionary path of NWDAF and the incorporation of intelligent RAN specifications as foundational milestones. Building on this foundation, the paper maps out essential standardization trajectories for 6G encompassing a paradigm shift from patchwork AI implementations to native AI design embedded from inception. Furthermore, it stresses the necessity of cross-domain AI consistency, enabling interoperable AI functions across heterogeneous network segments and multi-vendor environments. The establishment of service architectures supporting AI agent ecosystems and frameworks for cross-domain AI inference coordination are identified as strategic priorities to ensure scalable and efficient AI deployment.

In its concluding remarks, the study emphasizes that the proposed task-driven, principle-based design approach is not merely a theoretical exercise but a practical baseline fostering synergy among industry stakeholders. Realizing the full promise of 6G AI-native networks demands concerted efforts to forge consensus on functional specifications, procedural workflows, and interoperability standards. Such a unified vision will underpin the development and deployment of next-generation mobile networks that are intrinsically intelligent, adaptive, and seamless.

This paradigm shift to AI-native networking promises transformative benefits: network operators can leverage automated, context-aware system management that dynamically optimizes performance and resource allocation. Simultaneously, users and industries will gain access to robust AI-as-a-Service (AIaaS) ecosystems supported natively by the communication infrastructure, unlocking unprecedented possibilities in sectors ranging from healthcare to autonomous vehicles and immersive digital experiences. As the wireless industry prepares for this new frontier, the insights derived from this research illuminate a clear path forward toward the realization of truly intelligent, AI-empowered 6G networks.

As this foundational research is disseminated and debated within academic and industrial circles, the coming years will likely see accelerated innovation cycles, prototype deployments, and the formulation of global standards embodying the principles outlined. The 6G vision articulated here is not merely an extension of past wireless generations but a fundamental reimagining, aligning communication technology with the exponential advances in artificial intelligence. This synergy is destined to reshape how humans and machines connect, communicate, and collaborate in the digital age.

Subject of Research:
Integration of Artificial Intelligence as a foundational component in 6G mobile network architecture.

Article Title:
A Task-Driven Design Approach for 6G AI-Native Architecture

News Publication Date:
29-Jan-2026

Web References:

• Full paper: https://doi.org/10.1016/j.eng.2025.09.005
• Journal website: https://www.sciencedirect.com/journal/engineering

References:
Wang, X., Lu, L., Li, Q., Sun, Q., Shi, N., Chen, Z., & Sun, T. (2026). A Task-Driven Design Approach for 6G AI-Native Architecture. Engineering. https://doi.org/10.1016/j.eng.2025.09.005

Image Credits:
Xiaoyun Wang, Lu Lu, Qin Li, Qi Sun, Nanxiang Shi, Ziqi Chen, Tao Sun

Keywords

6G, AI-native architecture, mobile networks, artificial intelligence, network design, wireless communications, 3GPP, ITU-R IMT-2030, NWDAF, network orchestration, edge computing, AI-as-a-Service

The implications of such technology could be transformative, chiefly in sectors like healthcare and the autonomous vehicle industry, which are ever-evolving and require precise real-time data to function optimally. As the project coordinator, Antonio de la Oliva, highlights, the vision extends beyond merely enabling networks to facilitate communication. The goal is for these networks to become proactive observers capable of assessing their surroundings and responding dynamically to changing situations. This shift in functionality signifies a departure from traditional network roles, allowing for a comprehensive interconnected ecosystem where the network is aware of, and can respond to, real-world events.

A significant aspect of the MultiX initiative is focused on creating an energy-efficient network perception system, under the aegis of IMDEA Networks. This endeavor includes developing perception enablers that assist in localization and multi-static sensing across various radio technologies. One of the more intriguing technical elements that IMDEA Networks is tackling involves the integration of machine-learning algorithms designed to amalgamate distinct sensing modalities. This approach intends to extract enriched details concerning environmental objects. Joerg Widmer, the Research Director at IMDEA Networks, emphasizes the significance of multi-static and multi-band integrated sensing and communication (ISAC). According to Widmer, coherent integration is paramount for achieving high-precision environmental perception. Capturing signals from diverse viewpoints leads to improved spatial diversity, enhances micro-Doppler extraction capabilities, and yields richer motion signatures. Such advanced processing not only augments accuracy but also facilitates intelligent, real-time interactions with the environment.

The potential applications stemming from the MultiX project are diverse and groundbreaking. One notable application is the capacity of networks to ascertain elevated concentrations of individuals in specific areas, which could prove vital for crowd management and safety in public spaces. Furthermore, the technology could monitor safeguard conditions, such as detecting if an elderly person falls within their home. This capability could revolutionize how networks adapt by dynamically optimizing coverage distribution based on the immediate needs of users, thereby establishing a new standard in responsive connectivity.

Moreover, the project is not limited to healthcare; MultiX is actively exploring integration into industrial automation processes as well. According to de la Oliva, the aspiration is for networks to actuate the movement of robots in real time. This entails not only detecting obstacles but also enabling more effective task management by coordinating multiple robotic agents. This application could significantly enhance productivity in industrial settings by streamlining processes that currently require human oversight.

In parallel, the MultiX initiative also targets innovations in connected home health technologies. The vision is to develop contactless health monitoring systems that utilize connected home devices to track vital signs such as heart rate and respiration rates. Under this framework, the network could autonomously detect emergency scenarios, such as imminent heart attacks, leading to rapid alerts dispatched to healthcare services. The promise of such capabilities epitomizes the convergence of telecommunications and healthcare, potentially reshaping how we approach wellness and disease management in domestic settings.

Furthermore, sustainability remains a cornerstone of the MultiX project’s ethos, addressing one of the primary challenges that future 6G technologies must tackle. In pursuit of maximizing energy efficiency and curtailing resource consumption, the project leverages artificial intelligence to implement low-power solutions. This proactive approach not only aligns with global sustainability goals but also demonstrates an understanding that future networks must adapt to an evolving landscape increasingly focused on environmental responsibility.

To demonstrate the tangible benefits and capabilities of the technologies engendered from MultiX, the project intends to validate its findings through two critical proof-of-concept demonstrations. The initial proof involves creating a multilayer digital network twin aimed explicitly at optimizing processes within industrial manufacturing contexts. This model will serve as a testbed for refining and proving the efficacy of the project’s innovations. The second proof of concept will pivot towards contactless health monitoring technologies within the home, signifying a bold step toward transforming healthcare delivery models outside of traditional clinical environments.

Ultimately, these technologies, in conjunction with artificial intelligence enhancements, could lead to significant improvements in diagnostic accuracy and treatment effectiveness, even when conducted remotely. This potential evolution represents a paradigm shift in healthcare delivery, showcasing how integrated sensing and communication platforms could dramatically alter the fabric of home healthcare services.

MultiX, backed by the European Commission through the Horizon Europe program, is a strategic partnership involving a host of industry leaders and academic institutions. The consortium encompasses giants such as Apple Technology Engineering, Siemens AG, Telefónica S.A., and several esteemed universities. As the project unfolds, it sees participation from top-tier entities like INTEL, NEC Laboratories, and various research institutions, converging their expertise towards a common goal. Notably, Professor Antonio de la Oliva from UC3M serves as the Principal Investigator steering this collaborative research endeavor, with Valerio Frascolla from INTEL as the Innovation Director and Xi Li from NEC as the Technical Director.

Tenaciously ambitious, the MultiX project commenced its journey in January 2025, with the collective aspiration to complete its transformational work by June 2027. The work undertaken throughout this period promises to solidify the foundation for 6G technology’s integration into both everyday life and advanced industrial applications. As the project evolves, it holds the potential not only to reshape communication frameworks but also to lay the groundwork for the intricate relationship between technology and human interaction in an increasingly interconnected world.

Through the development of these novel systems, the MultiX initiative not only advocates for innovative technological solutions but also seeks to establish a blueprint for future networks that prioritize responsiveness, efficiency, and sustainability. As such, it represents a vital leap toward realizing a future where communication systems are not just functional but are integral, intelligent components of our daily realities.

Subject of Research: Integration of multisensory perception into communication networks for 6G technology
Article Title: MultiX: Redefining the Future of 6G Communication Networks
News Publication Date: October 2023
Web References:
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Image Credits:

Keywords