ETSI TS 128 100 V18.0.0 (2024-05)

5G; Management and orchestration; Levels of autonomous network (3GPP TS 28.100 version 18.0.0 Release 18)

RTS/TSGS-0528100vi00

General Information

• Status: Not Published
• Technical Committee: 3GPP SA 5 - Telecom Management
• Current Stage: 12 - Citation in the OJ (auto-insert)
• Completion Date: 15-May-2024

Standards Content (Sample)

TECHNICAL SPECIFICATION
5G;
Management and orchestration;
Levels of autonomous network
(3GPP TS 28.100 version 18.0.0 Release 18)

3GPP TS 28.100 version 18.0.0 Release 18 1 ETSI TS 128 100 V18.0.0 (2024-05)

Reference
RTS/TSGS-0528100vi00
Keywords
5G
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3GPP TS 28.100 version 18.0.0 Release 18 2 ETSI TS 128 100 V18.0.0 (2024-05)
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Modal verbs terminology
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Contents
Intellectual Property Rights . 2
Legal Notice . 2
Modal verbs terminology . 2
Foreword . 5
Introduction . 6
1 Scope . 7
2 References . 7
3 Definitions of terms, symbols and abbreviations . 7
3.1 Terms . 7
3.2 Symbols . 8
3.3 Abbreviations . 8
4 Concepts and background . 8
4.1 Autonomous network concept . 8
4.2 Autonomous network level concept . 8
4.3 Dimensions for evaluating autonomous network levels. . 8
4.3.1 Introduction. 8
4.3.2 Scenarios . 9
4.3.3 Management scope . 9
4.3.4 Workflow . 9
5 Framework approach for evaluating autonomous network levels . 10
6 Use cases and requirements . 12
6.1 Network and service planning scenarios . 12
6.2 Network and service deployment scenarios . 12
6.2.1 Autonomous network level for RAN NE deployment . 12
6.3 Network and service maintenance scenarios . 12
6.3.1 Autonomous network level for fault management . 12
6.4 Network and service optimization scenarios . 12
6.4.1 Autonomous network level for radio network coverage optimization . 12
6.4.2 Autonomous network level for RAN UE throughput optimization . 12
7 Generic autonomous network level . 13
7.1 Generic autonomous network level for network optimization . 13
7.1.1 Generic workflow . 13
7.1.2 Generic classification of autonomous network level . 13
7.1.3 Generic autonomy capability description for management system . 15
7.1.4 Generic MnS requirements . 16
7.1.4.1 MnS requirements to support autonomous network level 1 . 16
7.1.4.2 Additional MnS requirements to support autonomous network level 2 . 16
7.1.4.3 Additional MnS requirements to support autonomous network level 3 . 16
7.1.4.4 Additional MnS requirements to support autonomous network level 4 . 16
7.1.5 Solutions for generic MnS requirements . 16
7.2 Generic autonomous network level for RAN NE deployment . 17
7.2.1 Generic workflow . 17
7.2.2 Generic autonomous network level . 18
7.2.3 Generic autonomy capability description for management system . 19
7.2.4 Generic MnS requirements . 19
7.2.4.1 MnS requirements to support autonomous network level 1 . 19
7.2.4.2 Additional MnS requirements to support autonomous network level 2 . 20
7.2.4.3 Additional MnS requirements to support autonomous network level 3 . 20
7.2.4.4 Additional MnS requirements to support autonomous network level 4 . 20
7.2.5 Solutions for generic MnS requirements . 20
7.3 Generic autonomous network level for fault management . 20
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7.3.1 Generic workflow . 20
7.3.2 Generic autonomous network level . 21
7.3.3 Generic autonomy capability description for management system . 23
7.3.4 Generic MnS requirements . 23
7.3.4.1 MnS Requirements to support autonomous network level 1 . 23
7.3.4.2 Additional MnS requirements to support autonomous network level 2 . 24
7.3.4.3 Additional MnS requirements to support autonomous network level 3 . 24
7.3.4.4 Additional MnS requirements to support autonomous network level 4 . 24
7.3.5 Solutions for generic MnS requirements . 25
Annex A (informative): Examples of Autonomous network level for network and service
optimization . 26
A.1 Autonomous network level for radio network coverage optimization . 26
A.1.1 Workflow . 26
A.1.2 Classification of autonomous network level . 26
A.1.3 Example of mapping autonomous network level requirements for coverage optimization with
functional/interface features. 29
A.2 Autonomous network level for RAN UE throughput optimization . 29
A.2.1 Workflow . 29
A.2.2 Classification of autonomous network level . 30
Annex B (informative): Change history . 32
History . 33

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Foreword
This Technical Specification has been produced by the 3rd Generation Partnership Project (3GPP).
The contents of the present document are subject to continuing work within the TSG and may change following formal
TSG approval. Should the TSG modify the contents of the present document, it will be re-released by the TSG with an
identifying change of release date and an increase in version number as follows:
Version x.y.z
where:
x the first digit:
1 presented to TSG for information;
2 presented to TSG for approval;
3 or greater indicates TSG approved document under change control.
Y the second digit is incremented for all changes of substance, i.e. technical enhancements, corrections,
updates, etc.
z the third digit is incremented when editorial only changes have been incorporated in the document.
In the present document, modal verbs have the following meanings:
shall indicates a mandatory requirement to do something
shall not indicates an interdiction (prohibition) to do something
The constructions "shall" and "shall not" are confined to the context of normative provisions, and do not appear in
Technical Reports.
The constructions "must" and "must not" are not used as substitutes for "shall" and "shall not". Their use is avoided
insofar as possible, and they are not used in a normative context except in a direct citation from an external, referenced,
non-3GPP document, or so as to maintain continuity of style when extending or modifying the provisions of such a
referenced document.
Should indicates a recommendation to do something
should not indicates a recommendation not to do something
may indicates permission to do something
need not indicates permission not to do something
The construction "may not" is ambiguous and is not used in normative elements. The unambiguous constructions
"might not" or "shall not" are used instead, depending upon the meaning intended.
Can indicates that something is possible
cannot indicates that something is impossible
The constructions "can" and "cannot" are not substitutes for "may" and "need not".
Will indicates that something is certain or expected to happen as a result of action taken by an agency
the behaviour of which is outside the scope of the present document
will not indicates that something is certain or expected not to happen as a result of action taken by an
agency the behaviour of which is outside the scope of the present document
might indicates a likelihood that something will happen as a result of action taken by some agency the
behaviour of which is outside the scope of the present document
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might not indicates a likelihood that something will not happen as a result of action taken by some agency
the behaviour of which is outside the scope of the present document
In addition:
is (or any other verb in the indicative mood) indicates a statement of fact
is not (or any other negative verb in the indicative mood) indicates a statement of fact
The constructions "is" and "is not" do not indicate requirements.
Introduction
Autonomous network is one of the important topics in 5G network. Complexity of 5G network increases with large
number of devices and diversity of services. Different autonomous mechanisms are introduced by the industry to reduce
the complexity of mobile network and service management. Moving from a manual operating network to a fully
autonomous network requires a stepwise progression. For each step there are different capability and performance level
of autonomy. Thus the concept of autonomous network levels and corresponding requirements are introduced to
describe and evaluate each level in details.
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1 Scope
The present document specifies the concepts for autonomous networks, autonomous network level, and that use cases ,
requirements and solutions for the levels of autonomous functions in a 3GPP network.
2 References
The following documents contain provisions which, through reference in this text, constitute provisions of the present
document.
- References are either specific (identified by date of publication, edition number, version number, etc.) or
non-specific.
- For a specific reference, subsequent revisions do not apply.
- For a non-specific reference, the latest version applies. In the case of a reference to a 3GPP document (including
a GSM document), a non-specific reference implicitly refers to the latest version of that document in the same
Release as the present document.
[1] 3GPP TR 21.905: "Vocabulary for 3GPP Specifications".
[2] 3GPP TS 28.312: "Management and orchestration; Intent driven management services for mobile
networks".
[3] 3GPP TS 28.535: " Management and orchestration; Management Services for Communication
Service Assurance; Requirements".
[4] 3GPP TS 28.532: "Management and orchestration; Generic management services".
[5] 3GPP TS 28.541: "Management and orchestration; 5G Network Resource Model (NRM); Stage 2
and stage 3".
[6] 3GPP TS 28.622: "Telecommunication management; Generic Network Resource Model (NRM)
Integration Reference Point (IRP); Information Service (IS)".
[7] 3GPP TS 28.552: "Management and orchestration; 5G performance measurements".
[8] 3GPP TS 28.554: "Management and orchestration; 5G end to end Key Performance Indicators
(KPI)".
[9] 3GPP TS 32.422: "Telecommunication management; Subscriber and equipment trace; Trace
control and configuration management".
3 Definitions of terms, symbols and abbreviations
3.1 Terms
For the purposes of the present document, the terms given in TR 21.905 [1] and the following apply. A term defined in
the present document takes precedence over the definition of the same term, if any, in TR 21.905 [1].
Autonomous Network: telecommunication system (including management system and network) with autonomy
capabilities which is able to be governed by itself with minimal to no human intervention.
Autonomous Network Level: describes the level of autonomy capabilities in the autonomous network.
Network and Service Deployment: processes of allocation, installation, configuration, activation and verification of
specific network and service.
Network and Service Maintenance: processes of monitoring, analysing and healing of the network and service issues.
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Network and Service Optimization: processes of monitoring, analysing and optimizing the network and service
performance.
3.2 Symbols
Void.
3.3 Abbreviations
For the purposes of the present document, the abbreviations given in TR 21.905 [1] and the following apply. An
abbreviation defined in the present document takes precedence over the definition of the same abbreviation, if any, in
TR 21.905 [1].
ANL Autonomous Network Level
AON Autonomous Network
4 Concepts and background
4.1 Autonomous network concept
The network become complex due to large number of devices and diversity of services. Different autonomy
mechanisms are introduced in the industry to reduce the complexity of network management and control. The ultimate
goal for autonomous network is to enable telecommunication system (including management system and network) to be
governed by itself with minimal to no human intervention by utilizing the autonomy mechanisms (including intelligence
mechanism, e.g. AI/ML, and automation mechanism, e.g. rule-based automatic control, and other mechanisms to enable
the autonomous network). Autonomous network can reduce the operating expenditure (OPEX) associated with the
autonomous management and control of the complexity network and improve the service experience to enable various
vertical industries (e.g. autonomous vehicle, smart city). Following are concepts related to autonomous network:
- Autonomous network is telecommunication system (including management system and network) with autonomy
capabilities which is able to be governed by itself with minimal to no human intervention.
- Autonomous network level is used to describe the level of autonomy capabilities in the autonomous network.
- Self-Organization Network, Management data analytics, Intent driven management, closed loop SLS assurance
are examples of enablers for autonomous network.
4.2 Autonomous network level concept
Different autonomy mechanisms in the telecommunication system may lead to different capabilities of autonomy and
different operation efficiency on network management and control workflow, and indicates the level of autonomy of the
network. The term Autonomous network level is used to describe the levels of autonomy capabilities in the autonomous
network to improve the efficiency for network management and control. Participation of the human and
telecommunication system in the network management and control workflow are different for each level and are
important factors to evaluate the autonomous network levels. For each autonomous network level, some tasks can be
performed by telecommunication system, some performed by human, and some performed by cooperation of human
and telecommunication system. For example, in the highest autonomous network level, all tasks are performed by
telecommunication system.
4.3 Dimensions for evaluating autonomous network levels.
4.3.1 Introduction
This clause describes the dimensions i.e. scenarios, management scope and workflow, which can be used for evaluating
autonomous network level.
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4.3.2 Scenarios
The autonomous network can be implemented for different scenarios, the complexity of autonomous network depends
on the detailed scenarios where it is applied. Also it will be more challenging for the telecommunication system to
achieve the autonomous network for full scenarios than for certain scenarios. The autonomy capabilities of the scenarios
will impact the autonomous network level for the whole autonomous network.
Following are scenario types categorized by network and service management process for autonomous network:
- Network and service planning
- Network and service deployment
- Network and service maintenance
- Network and service optimization
NOTE: The network and service planning is not addressed in the present document.
4.3.3 Management scope
The autonomy can be implemented in different scopes, the complexity of autonomous network depends on its
applicable scope. For example, it will be more challenging for the telecommunication system to achieve the
autonomous network on cross domain network layer than domain network layer, because more autonomy mechanism
needs to be introduced for the coordination between different domains. The autonomy capabilities of the management
scope will impact the autonomous network level for the whole autonomous network.
Following are applicable scopes for autonomous network:
- Autonomy in NE/NF layer, which means the autonomy mechanisms are executed in the NE/NF.
- Autonomy in domain network layer, which means the autonomy mechanisms are executed in the MnF(s) in
domain.
- Autonomy in cross domain network layer, which means the autonomy mechanisms are executed in the MnF(s) in
cross domain.
- Autonomy in communication service layer, how to execute the autonomy mechanisms are executed in MnF(s)
for communication service.
Note: autonomy in communication service layer is not specified in the present document.

Figure 4.3.3-1: Autonomy for different management scope
4.3.4 Workflow
Workflow is used to describe the necessary steps to achieve certain management and control purposes. A workflow is
composed of one or more management and control tasks. Each workflow task may be accomplished by human, or
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accomplished by telecommunication system with human assistance, or accomplished by telecommunication system
without human intervention. The autonomy capabilities of the tasks in the workflow may impact the autonomous
network level.
Following are the categorization of the tasks in a workflow:
- Intent handling: The group of tasks which translate network or service intent from operator or customer into
detailed operations and/or control information which may affect one or more of the following groups of tasks (i.e.
awareness, analysis, decision, execution), also evaluate and feedback intent fulfilment information (e.g. the intent
is satisfied or not) based on the detailed network and service information. More information of intent handling see
the Intent driven management defined in 28.312[2].
- Awareness: The group of tasks which include network and service data (e.g. configuration data, performance
data, alarm data, etc.) collection and necessary data pre-processing (e.g. data cleaning, filtering, statistics, etc.)
with the purpose of monitoring network and service information (including network and service performance,
network and service anomaly, network and service event, etc.). More information of Awareness see
corresponding Monitor of Management control loops defined in 28.535 [3].
- Analysis: The group of tasks which analyse the obtained network and service information (e.g. network and
service status, network and service issues and so on) or based on the historical network and service information
to further predict the future change trend of the above network and service status, and make recommendation for
decision. More information of Analysis see corresponding Analytic of Management control loops defined in
28.535 [3].
- Decision: The group of tasks which evaluate and decide the necessary operation for execution, e.g. network
configuration or adjustment. More information of Decision see corresponding Decision of Management control
loops defined in 28.535 [3].
- Execution: The group of tasks which execute the operations. More information of Execution see corresponding
Execution of Management control loops defined in 28.535 [3].

Figure 4.3.4-1: Categorization of the tasks in the workflow for evaluating autonomous network levels
5 Framework approach for evaluating autonomous
network levels
A framework approach for evaluating autonomous network levels is as following, which is used for evaluating the
autonomy capability of telecom system. In the following framework table:
- "Human" represents corresponding tasks are accomplished by human or human utilizing the tools for network
and service management and orchestration.
- "Human & System" represents corresponding tasks are accomplished by collaboration of human and telecom
system, the detailed collaboration pattern depends on the scenario, which is not addressed in the framework
approach for evaluating autonomous network levels.
- "System" represents corresponding tasks are fully accomplished by telecom system.
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Table 5-1: Framework approach for evaluating autonomous network levels
Task categories
Autonomous network
level Execution Awareness Analysis Decision Intent handling
Manual operating
L0 Human Human Human Human Human
network
Assisted operating Human & Human &
L1 Human Human Human
network Telecom system Telecom system
Preliminary
Human & Human &
L2 autonomous Telecom system Human Human
Telecom system Telecom system
network
Intermediate
Human & Human &
L3 autonomous Telecom system Telecom system Human
Telecom system Telecom system
network
Advanced
Human &
L4 autonomous Telecom system Telecom system Telecom system Telecom system
Telecom system
network
Full autonomous
L5 Telecom system Telecom system Telecom system Telecom system Telecom system
network
NOTE 1: Human reviewed decision have the highest authority in each level if there is any confliction between human
reviewed decision and telecom system generated decision.
NOTE 2: The order of above five task categories does not reflect the workflow sequence.

Level 0 manual operating network: No categorization of the tasks is accomplished by telecom system itself.
Level 1 assisted operating network: A part of the execution and awareness tasks are accomplished automatically by
telecom system itself based on human defined control information. At this level, telecom system can assist human to
improve the execution and awareness efficiency.
Level 2 preliminary autonomous network: All the execution tasks are accomplished automatically by telecom system
itself. A part of the awareness and analysis tasks are accomplished automatically by telecom system itself based on human
defined control information. At this level, telecom system can assist human to achieve the closed loop based on human
defined control information.
Level 3 intermediate autonomous network: All the execution and awareness tasks are accomplished automatically by
telecom system itself. A part of the analysis and decision tasks are accomplished automatically by telecom system itself
based on human defined control information. At this level, the telecom system can achieve the closed loop automation
based on the human defined closed loop automation control information.
Level 4 advanced autonomous network: All the execution, awareness, analysis and decision tasks are accomplished
automatically by telecom system itself. And intent handling tasks can be partly accomplished automatically by telecom
system itself based on human defined intent handling control information. At this level, telecom system can achieve the
intent driven closed loop automation based on human defined intent handling control information, which means the
telecom system can translate the intent to the detailed closed loop automation control information and translate the detailed
network and service information to intent fulfilment information (e.g. the intent is satisfied or not) based on human defined
intent handling control information.
Level 5 fully autonomous network: The entire network autonomy workflow is accomplished automatically by telecom
system without human intervention. At this level, telecom system can achieve the whole network autonomy.
Note 1: Above framework approach for evaluating autonomous network levels is applicable for evaluating the
autonomous network level from both management scope and scenario perspective. The overall
autonomous network level of the whole telecom system is a comprehensive reflection of autonomous
network level of the individual management scope and scenarios, which means in fully autonomous
network level, the telecom system can achieve the whole network autonomy for all management scopes
and scenarios.
Note 2: The control information in the present document represents the information which can be formatted as rules
or policies to assist/control the system to perform corresponding tasks in an autonomous manner.
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6 Use cases and requirements
6.1 Network and service planning scenarios
NOTE: The Network and service planning scenarios is not addressed in the present document.
6.2 Network and service deployment scenarios
6.2.1 Autonomous network level for RAN NE deployment
RAN NE deployment use case refers to the entire workflow of deploying an RAN NE, full autonomy of RAN NE
deployment can help the network operator to reduce OPEX by reducing manual involvement in such tasks. However,
full autonomy of RAN NE deployment is a long term goal, it will be beneficial for operator to achieve this goal step by
step and have clear view on which typical issues can be addressed by utilizing network autonomy mechanisms in
corresponding steps. The requirements for each autonomous level for RAN NE deployment are different.
6.3 Network and service maintenance scenarios
6.3.1 Autonomous network level for fault management
Fault management use case refers to the entire workflow of network fault management, autonomy of fault management
can help the network operator to reduce OPEX by reducing manual involvement in such tasks and to enhance user
experience and reduce network and service failure time by reducing the time for network fault supervision and
recovery. However, full autonomy of fault management is a long term goal, it will be beneficial for operator to achieve
this goal step by step and have clear view on which typical issues can be addressed by utilizing network autonomy
mechanism in corresponding steps. The requirements for each autonomous level for fault management autonomy are
different.
6.4 Network and service optimization scenarios
6.4.1 Autonomous network level for radio network coverage optimization
Radio networks are geographically distributed, and mobile user activity varies significantly in different places and at
different times of day. To achieve the optimal coverage, a set of initial coverage configuration parameters (e.g.
coverageShape, digitalTilt and digitalAzimuth) may not always meet the requirements. Therefore, the coverage
configuration parameters need to be adjusted in a differentiated manner with the change of the radio network
environment. It is complex for the adjustment due to multiple factors needs to be considered, e.g. interference control,
huge data and frequent traffic changes. So introducing the autonomous network level for radio network coverage
optimization will benefit for operator to achieve the full autonomy goal step by step and have clear view on which
typical issues can be addressed by utilizing autonomy mechanism in corresponding steps. The requirements for each
autonomous level for radio network coverage optimization are different.
6.4.2 Autonomous network level for RAN UE throughput optimization
RAN UE throughput is a key performance for radio network, and, numerous radio feature parameters with broad
value ranges affect the RAN UE throughput. There are many radio feature parameters of RAN NE level or cell
level, for examples, MLB related parameters, resource schedule related parameters, cell reselection related
parameters, handover related parameters, different radio feature parameters affect each other and the combination
number of various parameter values is large. Therefore, it is complex to adjust radio feature configuration parameters
to achieve the optimized RAN UE throughput. So introducing the autonomous network level for RAN UE throughput
optimization will be benefit for operator to achieve the full autonomy goal step by step and have clear view on which
typical issues can be addressed by utilizing autonomy mechanism in corresponding steps. The requirements for each
autonomous level for RAN UE throughput optimization are different.
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7 Generic autonomous network level
7.1 Generic autonomous network level for network optimization
7.1.1 Generic workflow
Following is the generic entire workflow for the network optimization:
Intent handling:
- Task A: Network optimization control information generation and determination. The tasks of generating and
determining the network optimization related control information (e.g., control information for network issue
identification, network issue analysis and network parameters adjustment) based on received network optimization
intent (e.g. network targets for the specified areas).
- Task B: Network optimization intent fulfilment evaluation. The tasks of evaluating network optimization intent
fulfilment information (e.g. corresponding network targets are satisfied or not).
Awareness:
- Task C: Network related information collection. The tasks of collecting network related data, including network
performance data (i.e. performance measurement, MDT data), network configuration data and environment data
(e.g. electronic map)).
Analysis:
- Task D: Network issues identification. The tasks of analysing the network performance (e.g. geographical grid
based network performance) and identifying whether there are network issues (e.g. coverage related issues, RAN
UE throughput related issues).
- Task E: Network deterioration prediction. The tasks of analysing current network performance and historical
network performance, predicting the network performance trend in the future and identifying potential network
performance deterioration in advance.
- Task F: Network issue demarcation. The tasks of analyse the network issue and determine the network issue
categories (e.g. weak coverage, high load, low throughput).
- Task G: Network issue root cause analysis. The tasks of analysing the root cause (i.e. the location for the issue
occurs and the cause for the issue) of the identified or predicted network issues.
- Task H: Network adjustment solutions analysis. The tasks of generating the recommended network adjustment
solution which can address the identified or predicted network issues.
Decision:
- Task I: Network adjustment solutions evaluation and determination. The tasks of evaluating the recommended
network adjustment solutions, and deciding the network adjustment solutions to be executed.
Execution:
- Task J: Network adjustment solutions execution. The tasks of adjusting and configuring the network
configuration parameters.
7.1.2 Generic classification of autonomous network level
Level 0:
- All the tasks in the network optimization workflow (Task A, Task B, Task C, Task D, Task E, Task F, Task G,
Task H, Task I, Task J) are accomplished by human.
Level 1:
- Telecom system executes the tasks of network adjustment solutions execution based on the specified network
related parameters (Task J). Telecom system also can execute the tasks of collecting part of network related
ETSI
3GPP TS 28.100 version 18.0.0 Release 18 14 ETSI TS 128 100 V18.0.0 (2024-05)
information (including performance metrics, configuration data, MDT data) based on the specified collection
control information (Task C). At this level, telecom system can assist human to improve the execution and
awareness efficiency for network optimization.
- All the other tasks in the network optimization workflow (Task A, Task B, Task D, Task E, Task F, Task G,
Task H, Task I) are accomplished by human.
Level 2:
- Compared to Level 1, telecom system additionally executes the tasks of network issues identification, network
issue demarcation and network issue root cause analysis based on the specified network issue identification and
， Task G). In this level, telecom system also can execute the task of
analysis control information (Task D, Task F
collecting all network related information (including network performance data, network configuration data and
environment data) based on the specified collection control information(Task C),The tasks of network adjustment
solutions executio
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