



Network Working Group                                              M. Yu
Internet-Draft                                                   A. Wang
Intended status: Informational                                     J. Li
Expires: 16 July 2026                                              Z. Li
                                                           China Telecom
                                                         12 January 2026


           AI Agent Use Cases and Requirements in 6G Network
               draft-yu-dmsc-ai-agent-use-cases-in-6g-01

Abstract

   This draft introduces use cases related to AI Agents in 6G networks,
   primarily referencing the technical report of 3GPP SA1 R20 Study on
   6G Use Cases and Service Requirements (TR 22.870).  It also
   elaborates on some of the requirements for introducing AI Agents into
   6G networks from the perspective of operators.

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   This Internet-Draft will expire on 16 July 2026.

Copyright Notice

   Copyright (c) 2026 IETF Trust and the persons identified as the
   document authors.  All rights reserved.











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Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
   2.  Use Cases . . . . . . . . . . . . . . . . . . . . . . . . . .   3
     2.1.  Intent-based 6G Services Enabled by Network AI Agents . .   4
     2.2.  Device-Network Collaboration  . . . . . . . . . . . . . .   5
     2.3.  Multiple Devices Collaboration  . . . . . . . . . . . . .   5
     2.4.  Network-Application Collaboration . . . . . . . . . . . .   6
   3.  Potential Requirements for 6G Network . . . . . . . . . . . .   7
     3.1.  The Identity of AI Agents . . . . . . . . . . . . . . . .   7
     3.2.  Efficient Collaboration . . . . . . . . . . . . . . . . .   7
     3.3.  Cross-Domain Collaboration  . . . . . . . . . . . . . . .   7
     3.4.  Registration and Discovery  . . . . . . . . . . . . . . .   8
     3.5.  Service and Data Exposure . . . . . . . . . . . . . . . .   8
     3.6.  Reliability Assurance . . . . . . . . . . . . . . . . . .   8
     3.7.  High-performance Communication  . . . . . . . . . . . . .   8
     3.8.  Security  . . . . . . . . . . . . . . . . . . . . . . . .   8
     3.9.  Energy Efficiency . . . . . . . . . . . . . . . . . . . .   8
   4.  Conclusion  . . . . . . . . . . . . . . . . . . . . . . . . .   9
   5.  Informative References  . . . . . . . . . . . . . . . . . . .   9
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .   9

1.  Introduction

   Currently, with breakthroughs in large language models and multi-
   modal technologies, AI Agent has emerged as a major research focus in
   the industry.  Equipped with capabilities such as intent
   understanding, action planning, decision-making, task execution, and
   self-awareness, AI Agents can integrate environmental perception,
   memory, tool invocation, and multi-agent collaboration to accomplish
   complex tasks.  They have already demonstrated significant value in
   key fields like autonomous driving, intelligent customer service, and
   smart home systems.  In the 6G era, the introduction of AI Agent
   technology will enable operators to fully leverage the potential of
   mobile communication networks, significantly improving network
   operational efficiency and user experience.  As a result, AI Agents
   are expected to become a key research focus in future 6G networks,
   leading to deep integration between 6G and AI Agent technologies.




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   In the 3GPP R20 standardization research for 6G, AI Agent has been
   one of the most discussed and debated topics, whether in SA1's study
   on 6G scenarios and requirements or SA2's research on network
   architecture.  In the SA1#109 meeting, 19 contributions related to AI
   Agents were submitted, which include 16 new use cases, with 4 use
   cases ultimately agreed.  And a preliminary definition of AI Agent
   from a capability perspective was adopted: "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."  In the SA1#110 meeting, more
   than 30 contributions related to AI Agents were submitted, which
   include 22 new use cases, with 7 ultimately agreed.  In the SA2#172
   meeting, how to achieve deep integration of 6G network with AI
   technology (e.g. AI agent) has been explicitly included in the scope
   of 6G architecture study.

   This draft summarizes and categorizes the AI Agent-related use cases
   in 6G networks, with a brief introduction provided in Section 2.  In
   Section 3, from an operator's perspective, we elaborate on the
   potential requirements for introducing AI Agents into 6G networks,
   which should be considered when designing the agent communication
   related protocol in mobile communication network.  In Section 4, we
   conclude this draft.

2.  Use Cases

   AI Agents can be deployed at various locations within the 6G system.
   Depending on their deployment positions, AI Agents in 6G can be
   classified into On-device AI Agents, application AI Agents, network
   AI Agents, operation management AI Agents, etc.  For instance, on-
   device AI Agents refer to those implemented on end-user devices,
   while network AI Agents are those embedded within the 6G network.

   This section summarizes and categorizes AI Agent-related use cases in
   6G networks.  Unlike AI Agents in the Internet domain, use cases
   involving AI Agents in mobile communication networks place greater
   emphasis on how network AI Agents can deliver 6G services to users,
   as well as how different AI Agents within the 6G system coordinate
   with each other.











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2.1.  Intent-based 6G Services Enabled by Network AI Agents

   By deploying AI Agents within 6G network, the 6G network can provide
   users with intent-based services.  These intelligent services may
   represent combinations of multiple network capabilities, such as
   communication, sensing, AI/ML, computing, data and more.  Users only
   need to express their intent to the 6G network, without requiring
   specialized technical knowledge to decompose the intent into
   technical requirements.  In this context, 3GPP SA1 has formally
   defined network intent as: Expectations including requirements, goals
   and constraints without specifying how to achieve them.

   Use Case A: Network-Wide Intent Fulfilment

   The 6G system interprets high-level service intents and translate
   such intent into concrete actions, including resource selection,
   configuration, and coordination across communication, sensing,
   computing, AI, and data capabilities utilizing network AI Agents.

   Use Case B: Dynamic Service Customization and Optimization

   The 6G network AI Agents dynamically adapt and optimize service
   behavior based on real-time context information, user requirements,
   and operational conditions in order to maintain desired service
   objectives.

                                   +-------------+
                                   | User Intent |
                                   +------+------+
                                          |
                                 +--------v----------+
                                 | Network AI Agents |
                                 +--------+----------+
                                          |
                           +--------------v----------------+
                           |    Service Orchestration &    |
                           |      Resource Optimization    |
                           +-------------------------------+

                        Figure 2.1 Intent-Based Network Control











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2.2.  Device-Network Collaboration

   With the rapid advancement of technologies like smart phones and
   lightweight large-scale AI models, capabilities of user devices have
   significantly expanded, enabling autonomous execution of certain AI
   tasks and independent decision-making.  However, due to inherent
   device limitations - including constrained computational resources
   and battery capacity - deploying complex AI agents or performing
   sophisticated AI tasks locally on devices remains challenging.
   Consequently, investigating optimal collaboration mechanisms between
   UE-based AI agents and network-based AI agents to accomplish complex
   tasks represents a critical research direction for 6G networks.

   Use Case A: Enhanced UE Intelligence via Network Support

   The 6G system enables collaboration between on-device AI Agents and
   Network AI Agents such that devices can leverage network-provided
   context, analytics, and capabilities to improve local decision-making
   and task execution.

   Use Case B: Joint Device and Network Coordination Services

   On-device AI Agents and Network AI Agents jointly support
   coordination services in which adaptation decisions are distributed
   across device-side and network-side components.

        +-------------------+                  +-----------------------+
        | On-Device AI      | <--------------> | 6G Network AI Agents  |
        | Agent (UE)        |                  | and Network Support   |
        +-------------------+                  +-----------------------+
                  |                                        |
                  |                                        |
        +---------v---------+                  +-----------v----------+
        | Local Decisions   |                  | Network Capabilities |
        +-------------------+                  +----------------------+

                Figure 2.2 Device-Network AI Collaboration

2.3.  Multiple Devices Collaboration

   Under the powerful communication capabilities of 6G network, multiple
   on-device AI Agents can collaborate with each other to accomplish
   complex AI tasks.  These AI Agents may from either the same
   application or different applications.

   Use Case A: Cross-Device Intelligent Coordination





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   The 6G system securely exchanges information among multiple on-device
   AI Agents to enable coordinated task execution across devices.

   Use Case B: Group AI Agent Collaboration Domains

   The 6G system dynamically establishes the collaboration domains that
   allow authorized AI Agents to participate in group-based task
   execution under defined security and policy constraints.

 +-------------------+    +-------------------+    +-------------------+
 |   On-Device AI    |    |   On-Device AI    |    |   On-Device AI    |
 | Agent (Device 1)  |<-->| Agent (Device 2)  |<-->| Agent (Device N)  |
 +-------------------+    +-------------------+    +-------------------+
             \                    |                     /
              \                   |                    /
        +--------------------------------------------------------+
        | Dynamic Multi-Agent Secured Collaboration(DMSC) Domain |
        +--------------------------------------------------------+

              Figure 2.3 Multiple On-device AI Agents Collaboration

2.4.  Network-Application Collaboration

   The 6G network AI Agents and application AI Agents can fully
   collaborate to accomplish network tasks.  On one hand, AI agents
   within the 6G network can invoke appropriate application AI Agents
   based on service characteristics.  On the other hand, the network AI
   Agents can share network data and domain expertise with application
   AI Agents, providing crucial data support for application AI Agents.

   Use Case A: Integrated Service Orchestration

   The 6G system enables cooperation between Network AI Agents and
   application-layer AI Agents to support end-to-end service
   orchestration through context sharing and coordinated control
   actions.

   Use Case B: Knowledge-Driven AI Enhancements

   The 6G system provides mechanisms for exposing network-generated
   knowledge, such as sensing data and telemetry, to authorized AI
   Agents in support of advanced reasoning and service optimization.









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    +---------------------+                +-----------------------+
    |    Application      |                | 6G Network AI Agents  |
    |     AI Agents       |<-------------->|                       |
    +----------+----------+                +----------+------------+
               |                                      |
   +-----------v---------+                +-----------v------------------+
   | External Services   |                | Network Knowledge            |
   |  and Applications   |                | (Sensing, AI, Computing,etc) |
   +---------------------+                +------------------------------+

          Figure 2.4 Network-Application AI Collaboration

3.  Potential Requirements for 6G Network

   In this section, we present potential requirements to 6G network that
   may arise from the introduction of AI Agents in 6G mobile
   communication network from an operator's perspective.  Some of these
   potential requirements have already been agreed by 3GPP, while others
   have not yet been adopted by 3GPP.

3.1.  The Identity of AI Agents

   The 6G network shall support secure authentication, authorization,
   and management mechanisms for AI Agents' digital identities.  These
   AI Agents include on-device AI Agents, 3rd party AI Agents, Network
   AI Agents, etc.  A robust identity management mechanism is the
   prerequisite for interactions between users and AI Agents, as well as
   between different AI Agents.

3.2.  Efficient Collaboration

   The 6G network shall support efficient collaboration between
   different AI Agents and between AI Agents and the tools.  This
   include: developing agent communication protocols better suited for
   6G network characteristics, supporting multi-modal data (such as
   text, audio, video, etc.) interactions, enabling rapid transmission
   of massive data volumes, etc.

3.3.  Cross-Domain Collaboration

   Future AI agents will be ubiquitous, forming a device-network-
   industry end-to-end ecosystem. 6G network shall support the cross-
   domain collaboration of AI agents, including the device domain, RAN
   domain, core network domain, operation and management domain,
   application domain, etc.






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3.4.  Registration and Discovery

   The 6G network shall support mechanisms for on-device AI Agents, 3rd
   party AI Agent, Network AI Agents and tools to register their
   attributes to 6G network, which enables efficient, cross-platforms
   and cross-domain AI Agents and tools discovery.  This may different
   from the discovery mechanism in existing agent communication related
   protocol (e.g. NRF discovery mechanism).

3.5.  Service and Data Exposure

   The 6G network shall support secure mechanisms to expose the 6G
   services (e.g. sensing service, computing service, AI/ML service,
   etc.) and network data (e.g. sensing data, positioning data, etc.) to
   3rd party AI Agents.

3.6.  Reliability Assurance

   The 6G network shall be able to provide mechanisms (e.g. network
   digital twin) to ensure the reliability and the validity of the
   decisions made by the AI Agents.  The decisions made by the AI Agents
   in 6G network may directly change the network status, parameters,
   configurations.  Only decisions that have been verified for
   reliability can be executed to change the network environment.

3.7.  High-performance Communication

   The 6G network shall enable high-performance communication, which may
   include low latency, high band-width, ultra-high data rate, etc.
   This is crucial for numerous scenarios such as device-network
   collaboration, network-application collaboration.

3.8.  Security

   The security of AI Agents communication in 6G includes the data
   protection and user consent.  Data privacy means the 6G network shall
   support end-to-end encryption for the interactions between AI Agents
   to ensure robust data protection and privacy security for sensitive
   information.  Besides, 6G network shall be able to provide mechanisms
   to collect the user consent for the local data collection.

3.9.  Energy Efficiency

   The 6G network shall be able to provide mechanisms to optimize the
   communication between AI Agents (especially for the on-device AI
   Agents) to reduce energy consumption.





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4.  Conclusion

   AI Agents are expected to represent a critical innovation vector for
   6G.  This draft explores the transformative potential of AI Agents in
   6G network, outlining key use cases and operational requirements from
   an operator's perspective.  When designing agent communication
   related protocols for 6G network, the aforementioned requirements
   should be thoroughly considered and incorporated into the protocol
   architecture.

5.  Informative References

   [TR_22.870]
              "3GPP TR 22.870, "Study on 6G Use Cases and Service
              Requirements", 2025.".

Authors' Addresses

   Menghan Yu
   China Telecom
   Beiqijia Town, Changping District
   Beijing
   Beijing, 102209
   China
   Email: yumh1@chinatelecom.cn


   Aijun Wang
   China Telecom
   Beiqijia Town, Changping District
   Beijing
   Beijing, 102209
   China
   Email: wangaj3@chinatelecom.cn


   Jinyan Li
   China Telecom
   Beiqijia Town, Changping District
   Beijing
   Beijing, 102209
   China
   Email: lijinyan@chinatelecom.cn


   Zhen Li
   China Telecom
   Beiqijia Town, Changping District



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   Beijing
   Beijing, 102209
   China
   Email: liz779@chinatelecom.cn















































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