



Network Working Group                                    E. Stephan, Ed.
Internet-Draft                                                    Orange
Intended status: Informational                                 R. Schott
Expires: 8 January 2026                                 Deutsche Telekom
                                                                D. Lopez
                                                              Telefonica
                                                                 X. Duan
                                                            China Mobile
                                                               L. Morand
                                                                  Huawei
                                                             7 July 2025


                   AI Agent protocols for 6G systems
                      draft-stephan-ai-agent-6g-00

Abstract

   Communication between AI agents and between agent and tools is
   expected to be pivotal in 6G systems.  The 3GPP TR 22.870 outlines
   various use cases and potential service requirements for AI agent
   communication within 6G systems.  This document provides examples of
   use cases and service requirements contained in the 3GPP TR 22.870
   and extrapolates possible requirements related to agent communication
   protocols.

Status of This Memo

   This Internet-Draft is submitted in full conformance with the
   provisions of BCP 78 and BCP 79.

   Internet-Drafts are working documents of the Internet Engineering
   Task Force (IETF).  Note that other groups may also distribute
   working documents as Internet-Drafts.  The list of current Internet-
   Drafts is at https://datatracker.ietf.org/drafts/current/.

   Internet-Drafts are draft documents valid for a maximum of six months
   and may be updated, replaced, or obsoleted by other documents at any
   time.  It is inappropriate to use Internet-Drafts as reference
   material or to cite them other than as "work in progress."

   This Internet-Draft will expire on 8 January 2026.

Copyright Notice

   Copyright (c) 2025 IETF Trust and the persons identified as the
   document authors.  All rights reserved.




Stephan, et al.          Expires 8 January 2026                 [Page 1]

Internet-Draft           Agent protocols for 6G                July 2025


   This document is subject to BCP 78 and the IETF Trust's Legal
   Provisions Relating to IETF Documents (https://trustee.ietf.org/
   license-info) in effect on the date of publication of this document.
   Please review these documents carefully, as they describe your rights
   and restrictions with respect to this document.  Code Components
   extracted from this document must include Revised BSD License text as
   described in Section 4.e of the Trust Legal Provisions and are
   provided without warranty as described in the Revised BSD License.

Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
   2.  AI Agent related use cases in the context of 6G . . . . . . .   4
     2.1.  General . . . . . . . . . . . . . . . . . . . . . . . . .   4
     2.2.  Network Optimization and Management . . . . . . . . . . .   5
     2.3.  Immersive Communications  . . . . . . . . . . . . . . . .   5
     2.4.  Hyper-Reliable Low-Latency Communications . . . . . . . .   5
     2.5.  Massive IoT Device Communications . . . . . . . . . . . .   6
     2.6.  Security and Privacy  . . . . . . . . . . . . . . . . . .   6
     2.7.  Autonomous Systems  . . . . . . . . . . . . . . . . . . .   6
     2.8.  AI Agent Collaboration  . . . . . . . . . . . . . . . . .   6
   3.  Potential agent communications related requirements . . . . .   7
     3.1.  General . . . . . . . . . . . . . . . . . . . . . . . . .   7
     3.2.  Interoperability  . . . . . . . . . . . . . . . . . . . .   7
       3.2.1.  Standardized Protocols  . . . . . . . . . . . . . . .   7
       3.2.2.  Multimodal Data Formats . . . . . . . . . . . . . . .   7
       3.2.3.  Agent Identity Management . . . . . . . . . . . . . .   7
     3.3.  Discovery Mechanisms  . . . . . . . . . . . . . . . . . .   7
     3.4.  Task Management . . . . . . . . . . . . . . . . . . . . .   8
     3.5.  Context Awareness . . . . . . . . . . . . . . . . . . . .   8
       3.5.1.  Contextual Understanding  . . . . . . . . . . . . . .   8
       3.5.2.  Adaptive Communication  . . . . . . . . . . . . . . .   8
     3.6.  Autonomy  . . . . . . . . . . . . . . . . . . . . . . . .   8
       3.6.1.  Decision Making . . . . . . . . . . . . . . . . . . .   8
       3.6.2.  Self-Management . . . . . . . . . . . . . . . . . . .   8
     3.7.  Security  . . . . . . . . . . . . . . . . . . . . . . . .   8
       3.7.1.  Authentication and Authorization  . . . . . . . . . .   8
       3.7.2.  Data Protection . . . . . . . . . . . . . . . . . . .   9
       3.7.3.  User Consent  . . . . . . . . . . . . . . . . . . . .   9
     3.8.  Low Latency Communication . . . . . . . . . . . . . . . .   9
     3.9.  Reliability . . . . . . . . . . . . . . . . . . . . . . .   9
       3.9.1.  Fault Tolerance . . . . . . . . . . . . . . . . . . .   9
       3.9.2.  Load Balancing  . . . . . . . . . . . . . . . . . . .   9
       3.9.3.  Redundancy  . . . . . . . . . . . . . . . . . . . . .   9
     3.10. Flexibility . . . . . . . . . . . . . . . . . . . . . . .   9
       3.10.1.  Scalability  . . . . . . . . . . . . . . . . . . . .  10
       3.10.2.  Adaptability . . . . . . . . . . . . . . . . . . . .  10
       3.10.3.  Extensibility  . . . . . . . . . . . . . . . . . . .  10



Stephan, et al.          Expires 8 January 2026                 [Page 2]

Internet-Draft           Agent protocols for 6G                July 2025


     3.11. Energy Efficiency . . . . . . . . . . . . . . . . . . . .  10
       3.11.1.  Optimized Communication  . . . . . . . . . . . . . .  10
       3.11.2.  Power Management . . . . . . . . . . . . . . . . . .  10
   4.  Conclusions . . . . . . . . . . . . . . . . . . . . . . . . .  10
   5.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .  11
   6.  Security Considerations . . . . . . . . . . . . . . . . . . .  11
   7.  References  . . . . . . . . . . . . . . . . . . . . . . . . .  11
     7.1.  Informative References  . . . . . . . . . . . . . . . . .  11
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  12

1.  Introduction

   Since 1998, the 3rd Generation Partnership Project (3GPP) has been
   fundamental in the development of standards for various generations
   of mobile networks, including 3G, 4G (LTE), and 5G.

   5G has revolutionized the way we connect, offering unprecedented
   throughput, low latency, and the capacity to handle a vast number of
   connected devices, thus driving innovation in the consumer market and
   various verticals such as healthcare, automotive, industrial
   automation, satellite and smart cities.  Unlike traditional networks
   that rely on point-to-point interfaces, the 5G core network has been
   designed as a cloud-native service-based architecture with network
   functions communicating each other using RESTful APIs over HTTP/2.
   These network functions can be deployed and managed dynamically,
   leveraging cloud technologies such as virtualization,
   containerization, and microservices.  This modularity allows for more
   agile, scalable, and efficient network operations.

   Whereas these existing standards are still being enhanced to meet the
   growing demands of the telecommunications industry, the 3GPP has
   already undertaken a deep exploratory work on the use cases, service
   requirements and system architecture for 6G.  This study phase will
   be then followed by a normative work to be completed by 2030 to meet
   ITU-R IMT 2030 timeline [M.2160].

   6G aims to support societal advancements and to bring value to
   society in the 2030s and beyond in secure, resilient, environmentally
   and economically sustainable ways.  In addition to new 6G services,
   other considerations are needed, e.g. CAPEX/OPEX reduction,
   improvement of overall 3GPP system performance, and migration from
   and interworking with 5G aspects.

   A study on service requirements and use cases for 6G is documented in
   the 3GPP Technical Report (TR) 22.870 [TR22.870].  While at an early
   stage and the document being still a work in progress, the current
   content of the report already provides useful insights on the
   potential foundation pillars of the new 6G system.  One of them being



Stephan, et al.          Expires 8 January 2026                 [Page 3]

Internet-Draft           Agent protocols for 6G                July 2025


   the Artificial Intelligence (AI) and how 6G could leverage AI and
   machine learning to enhance mobile network capabilities, service
   offering and user experience.

2.  AI Agent related use cases in the context of 6G

2.1.  General

   The recommendation ITU-R Recommendation M.2160-0 [M.2160] provides a
   comprehensive framework for the development of 6G technologies,
   focusing on the capabilities and objectives that these technologies
   should achieve around 2030 and beyond.  In this document, the
   integration of AI in telecommunications is poised to be a cornerstone
   for the development of 6G systems.  AI is considered as a
   foundational element, supporting both the network infrastructure and
   devices in delivering 3GPP services, often referred to as "AI for 6G
   system".  Additionally, mobile network capabilities are aimed to be
   enhanced and optimized for supporting AI applications, termed "6G
   system for AI".

   AI is not a novel concept within 3GPP, which has been actively
   engaged in standardizing AI and machine learning (ML) capabilities
   within 5G systems.  These efforts span various domains, including
   management and orchestration, core networks, and next-generation
   radio access networks (NG-RAN).  The objective is to boost system
   performance, efficiency, and the overall end-user experience.  This
   ongoing work is crucial not only for current 5G advancements but also
   sets a solid foundation for future 6G technologies.

   Beyond traditional AI/ML capabilities, 3GPP is exploring the
   integration of AI agents in 6G systems.  According to 3GPP TR 22.870
   [TR22.870], an AI agent is defined as follows:

   Al Agent:
      an automated intelligent entity capable of e.g interacting with
      its environment, acquiring contextual information, reasoning,
      self-learning, decision-making, executing tasks (autonomously or
      in collaboration with other Al Agents) to achieve a specific goal.

   AI agents are anticipated to enhance network efficiency by
   dynamically optimizing resources, predicting network conditions, and
   ensuring seamless communication between services.  By incorporating
   large language models (LLMs), AI agents could interpret complex
   requests, convert them into actionable insights, and orchestrate
   advanced 3GPP services such as immersive communication, sensing, and
   computing services.  It is also expected that these agents would be
   able to communicate, coordinate, and cooperate with other agents to
   tackle tasks that a single agent would struggle with.



Stephan, et al.          Expires 8 January 2026                 [Page 4]

Internet-Draft           Agent protocols for 6G                July 2025


   In this context, communication between AI agents is expected to be
   pivotal in the 6G system, by enabling advanced network
   functionalities to enhance the existing capabilities of 5G networks,
   providing more efficient, reliable, and secure communication
   services.  The 3GPP TR 22.870 [TR22.870] outlines various use cases
   and potential service requirements for AI agent communication
   protocols within the 6G framework.  Some of these use cases are
   provided in the following sections.  They are only provided for
   information and are subject to change till the completion of the
   study.

2.2.  Network Optimization and Management

   *  AI-Driven Network Slicing: AI agents in the 6G system should be
      able to communicate with 3rd-party AI agent to dynamically manage
      and optimize network slices, ensuring efficient resource
      allocation and improved performance for different services and
      applications.

   *  Predictive Maintenance: AI agents deployed in the 6G systems
      should be able to share information to predict potential network
      failures and perform preventive maintenance, reducing downtime and
      enhancing network reliability.

2.3.  Immersive Communications

   *  Traffic Management: AI agents should be able to communicate with
      other agents and tools to analyze and predict traffic patterns,
      optimizing bandwidth allocation and ensuring high-quality service
      for users, especially in densely populated areas.

   *  Quality of Experience (QoE) Optimization: AI agents should be able
      to collaborate to monitor and adjust network parameters in real-
      time, enhancing the user experience for high-bandwidth
      applications like video streaming and virtual reality.

2.4.  Hyper-Reliable Low-Latency Communications

   *  Real-Time Decision Making: AI agents should be able to facilitate
      real-time decision-making processes in critical applications such
      as autonomous driving, industrial automation, and remote surgery,
      where ultra-low latency and high reliability are crucial.

   *  Fault Detection and Recovery: AI agents should be able to quickly
      detect and recover from faults, maintaining the high reliability
      required for mission-critical applications.





Stephan, et al.          Expires 8 January 2026                 [Page 5]

Internet-Draft           Agent protocols for 6G                July 2025


2.5.  Massive IoT Device Communications

   *  Device Management: AI agents distributed in the network (terminal,
      edge, core, etc.) should be able to collaborate to manage a large
      number of IoT devices, optimizing their connectivity and power
      consumption to extend battery life and improve network efficiency.

   *  Data Analytics: AI agents should be able to collaborate to share
      and analyze data from IoT devices to provide insights and support
      decision-making processes in various applications, such as smart
      cities, agriculture, and healthcare.

2.6.  Security and Privacy

   *  Anomaly Detection: AI agents should be able to exchange
      information about anomalous behavior detection and potential
      security threats in real-time, enhancing the overall security of
      the network.

   *  Privacy Preservation: AI agents should be able to implement and
      share privacy-preserving techniques to protect user data, maintain
      sensitive data within individual networks, and ensure compliance
      with regulatory requirements.

2.7.  Autonomous Systems

   *  Autonomous Vehicles: Embedded AI agents should be able to
      communicate inside the same vehicle, between vehicles, between
      vehicles and the network for decision making based on environment
      perception, trajectory planning, and complex real-time control.

   *  Industrial Automation: AI agents should be able to communicate to
      optimize and control industrial processes, improving efficiency
      and reducing operational costs.

2.8.  AI Agent Collaboration

   *  AI agent communication groups: Groups of User AI agents (AI
      assistant, drone, intelligent vehicle, home robot, etc.) could be
      dynamically created to allow the communication between AI agents
      to complete complex tasks requested by a user and/or between
      multiple user AI agent groups, owned by different users, across
      diverse locations ranging from local wireless networks to the wide
      area networks.

   *  Intelligent Communication Assistants: Operators can advantageously
      provide Intelligent Communication Assistant services to their
      subscribers.  Intelligent Communication Assistant could understand



Stephan, et al.          Expires 8 January 2026                 [Page 6]

Internet-Draft           Agent protocols for 6G                July 2025


      user intention by collecting multi-modal data of the user and
      execute the user instructions by invoking other AI assistants and
      services provided by the 3rd party service provider.

3.  Potential agent communications related requirements

3.1.  General

   Agent communication in the context of AI and 6G networks involves
   several common requirements to ensure effective, efficient, and
   secure interactions between users and agents, between agents and
   between agents and tools.  Here is a list of potential key
   requirements derived from the illustrative use cases provided in the
   previous sections.  They are not yet formally approved by 3GPP and
   only provided for information/discussion.

3.2.  Interoperability

3.2.1.  Standardized Protocols

   Agents should be able to use standardized communication protocols to
   ensure they can interact seamlessly across different platforms and
   systems.  Agents should also support a standard protocol to interact
   with external data sources (e.g. user data repository) and AI-powered
   tools (e.g. location services) to complete their tasks.

3.2.2.  Multimodal Data Formats

   Agents should be able to support multimodal data formats (e.g., text,
   file, real-time audio stream, video streaming) to facilitate easy
   data exchange and interpretation.

3.2.3.  Agent Identity Management

   To allow the communication between users and agents as well as
   between agents and/or tools across platforms/domains, the system
   should support secure mechanisms for identification, verification and
   governance of agents/tools identities.

3.3.  Discovery Mechanisms

   Robust and efficient AI agent and tool discovery mechanisms to
   dynamically identify and locate AI agents/tools across different
   platforms and organizations.  It should be possible to combine
   multiple discovery mechanisms depending on specific requirements and
   constraints of the application domain, e.g. broadcasting/
   multicasting-based mechanisms for intra-domain discovery and use of
   centralized directories for cross-domain discovery.



Stephan, et al.          Expires 8 January 2026                 [Page 7]

Internet-Draft           Agent protocols for 6G                July 2025


3.4.  Task Management

   AI agent communication should provide a robust and efficient task
   management to enable seamless coordination and collaboration among
   agents.  Task management includes task decomposition (complex tasks
   broken down into smaller sub-tasks that can be executed by individual
   agents or groups of agents), task assignment (based on agent
   capabilities, availability, workload), task scheduling, task
   coordination among agents and task monitoring/tracking.

3.5.  Context Awareness

3.5.1.  Contextual Understanding

   Agents should be aware of the context in which they operate,
   including the state of other agents and the environment, to make
   informed decisions.

3.5.2.  Adaptive Communication

   Agents should be able to adapt the communication based on the context
   and current needs of the system.

3.6.  Autonomy

3.6.1.  Decision Making

   Agents should be capable of making autonomous decisions based on data
   analysis and reinforcement learning but also making collaborative
   decisions based on dynamic interaction between agents.

3.6.2.  Self-Management

   Capabilities for self-management, including self-configuration, self-
   optimization, and self-healing based on information received from
   other agents.

3.7.  Security

3.7.1.  Authentication and Authorization

   The agent communications should support authentication mechanisms for
   agent identity verification and authorization mechanisms to grant or
   deny access to specific resources based on the authenticated agent's
   permissions or roles.  These mechanisms should be applicable for
   intra-domain and cross-domain scenarios.





Stephan, et al.          Expires 8 January 2026                 [Page 8]

Internet-Draft           Agent protocols for 6G                July 2025


3.7.2.  Data Protection

   The agent communications should support encryption mechanism to
   protect sensitive data from unauthorized access, ensuring privacy and
   confidentiality.

3.7.3.  User Consent

   The agent communication should provide mechanism to collect the user
   consent for the secure exchange of personal sensitive data with an AI
   agent (e.g. AI assistant) inside the network or 3rd-party application
   domain and between AI agents.

3.8.  Low Latency Communication

   The agent communication should enable minimal delay data
   transmission, especially critical for real-time applications like
   industrial automation, robotics, or real-time gaming, to reduce lag
   and improve service experience.

3.9.  Reliability

3.9.1.  Fault Tolerance

   The agent communication should support mechanisms to detect, mitigate
   and recover from communication anomalies that would undermine
   collective decision making between agents.  These anomalies include
   message storms, communication deadlocks, protocol violations, or
   content inconsistencies.

3.9.2.  Load Balancing

   Agent communication protocols should be able support load-balancing
   among agents to prevent any single agent from becoming a bottleneck
   and maintain continuous operation.

3.9.3.  Redundancy

   Redundancy mechanisms (e.g. active/passive redundancy, data
   redundancy, georedundancy) should be implemented to ensure high-
   reliability, resilience and service continuity even if one or several
   agents fail.

3.10.  Flexibility







Stephan, et al.          Expires 8 January 2026                 [Page 9]

Internet-Draft           Agent protocols for 6G                July 2025


3.10.1.  Scalability

   Agent communication protocols should be designed to accommodate
   increasing network sizes and data volumes without significant
   performance degradation, even during peak load events.

3.10.2.  Adaptability

   Agent communication protocols should be able to adjust to multiple
   contexts (including heterogeneous agent capabilities, service
   environment, system requirements), multiple ways of transmitting
   information, including verbal, non-verbal, written, and visual forms,
   used individually or in combination, as well as the location of the
   AI agents (in the user terminal, in the network, in the 3rd party
   service environment).

3.10.3.  Extensibility

   For onward compatibility, agent communication protocols should be
   able to evolve and adapt to new technologies and service requirements
   without requiring major overhauls.

3.11.  Energy Efficiency

3.11.1.  Optimized Communication

   Agent communication should support mechanisms to optimize
   communication between embedded AI agents to reduce energy
   consumption, especially important for battery-powered devices (e.g.
   IoT devices).

3.11.2.  Power Management

   Agent communication should support efficient power management
   strategies to extend the operational life of devices embedding AI
   agents.

4.  Conclusions

   AI agents are envisioned to enhance network efficiency by dynamically
   optimizing resources, predicting network conditions, and facilitating
   seamless communication between services.  The incorporation of large
   language models (LLMs) will enable AI agents to understand complex
   requests and orchestrate advanced services, further enhancing the
   capabilities of 6G networks.






Stephan, et al.          Expires 8 January 2026                [Page 10]

Internet-Draft           Agent protocols for 6G                July 2025


   AI agent communication is expected to play a crucial role in enabling
   advanced network functionalities.  The use cases outlined in 3GPP TR
   22.870 [TR22.870] demonstrate the potential of AI agent communication
   to enhance the existing capabilities of 5G networks, providing more
   efficient, reliable, and secure communication services.

   In summary, the integration of AI in 6G systems represents a
   significant advancement in telecommunications technology.  The
   ongoing work by 3GPP in standardizing AI capabilities and exploring
   the potential of AI agents highlights the transformative impact that
   AI is expected to have on future network infrastructures and
   services.

   If a multi-AI agent-based system is formally adopted by 3GPP in the
   scope of 6G, standard solutions will be required to support secure
   and reliable communication between agents and between agents and
   external tools.  These solutions will be used inside the 3GPP system
   but also with 3rd-party platforms.  It is then required to have
   solutions developed by standard organizations that would be widely
   adopted by the AI development community.  It is foreseen that IETF
   could be the right place to develop and maintain such standard
   protocols.  If such standardization work is eventually endorsed by
   IETF, a close coordination between IETF and 3GPP will be essential to
   ensure that any AI agent communication protocols specified by IETF
   will support specific functional and service requirements defined by
   3GPP in the 6G context.  And it is also expected that this work will
   be completed in a timely manner to cope with the challenging workplan
   defined by 3GPP for the development of a 6G system in the ITU-R IMT
   2030 framework [M.2160].

5.  IANA Considerations

   This memo includes no request to IANA.

6.  Security Considerations

   This document should not affect the security of the Internet.

7.  References

7.1.  Informative References

   [TR22.870] 3GPP, "3GPP TR 22.870: Study on 6G Use Cases and Service
              Requirements; Stage 1 (Release 20)",
              <https://www.3gpp.org/ftp/Specs/archive/22_series/22.870>.






Stephan, et al.          Expires 8 January 2026                [Page 11]

Internet-Draft           Agent protocols for 6G                July 2025


   [M.2160]   ITU-R, "Recommendation ITU-R M.2160-0: Framework and
              overall objectives of the future development of IMT for
              2030 and beyond", <https://www.itu.int/dms_pubrec/itu-
              r/rec/m/R-REC-M.2160-0-202311-I!!PDF-E.pdf>.

Authors' Addresses

   Emile Stephan (editor)
   Orange
   2, avenue Pierre Marzin
   22300 Lannion
   France
   Email: emile.stephan@orange.com


   Roland Schott
   Deutsche Telekom
   Deutsche-Telekom-Allee 9
   64295 Darmstadt
   Germany
   Email: Roland.Schott@telekom.de


   Diego Lopez
   Telefonica
   Email: diego.r.lopez@telefonica.com


   Xiaodong Duan
   China Mobile
   Email: duanxiaodong@chinamobile.com


   Lionel Morand
   Huawei
   18 QUAI DU POINT DU JOUR
   92100 BOULOGNE-BILLANCOURT
   France
   Email: lionel.morand@huawei.com












Stephan, et al.          Expires 8 January 2026                [Page 12]
