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10.2.9.3 Application Errors
No additional application errors defined in the present document.
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10.3 AI/ML model training API
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10.3.1 Introduction
This API enables the API Consumer to request AI/ML model training, query AI/ML model training job status, and cancel AI/ML model training based on the procedures for "AI/ML model training services" as defined in R1GAP [5]. It also allows the API Producer to notify AI/ML model training job status change based on the pro...
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10.3.2 API version
For the AI/ML model training API as specified in the present document, the MAJOR version field shall be 1, the MINOR version field shall be 0, and the PATCH version field shall be 0 (see ETSI TS 129 501 [1] for a definition of the version fields). Consequently, the <apiVersion> URI path segment shall be set to "v1". Th...
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10.3.3 Resource structure and methods
The request URIs used in HTTP requests from the API Consumer towards the API Producer shall have the resource URI structure as defined in clause 5.2. The <apiName> resource URI variable shall be "ai-ml-model-training". Figure 10.3.3-1 shows the overall resource URI structure defined for the AI/ML model training API. Fi...
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10.3.4 Service operations
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10.3.4.1 Request AI/ML model training
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10.3.4.1.1 Operation definition
The API Consumer uses this operation to request AI/ML model training. The operation to create AI/ML model training job is based on HTTP POST. {apiRoot}/ai-ml-model-training/<apiVersion> /training-jobs /{trainingJoblId} /status ETSI ETSI TS 104 231 V8.0.0 (2026-03) 132 Figure 10.3.4.1.1-1: Request AI/ML model training o...
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10.3.4.1.2 Referenced procedures
10.3.4.1.2.1 Request AI/ML model training procedure The request AI/ML model training operation illustrated in Figure 10.3.4.1.1-1 is based on the request AI/ML model training procedure defined in R1GAP [5].
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10.3.4.2 Cancel AI/ML model training
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10.3.4.2.1 Operation definition
The API Consumer uses this operation to cancel AI/ML model training. The operation to delete AI/ML model training job is based on HTTP DELETE. Figure 10.3.4.2.1-1: Cancel AI/ML model training operation The service operation is as follows: 1) The API Consumer shall send an HTTP DELETE request to the API Producer. The ta...
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10.3.4.2.2 Referenced procedures
10.3.4.2.2.1 Cancel AI/ML model training procedure The cancel AI/ML model training operation illustrated in Figure 10.3.4.2.1-1 is based on the cancel AI/ML model training procedure defined in R1GAP [5].
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10.3.4.3 Query AI/ML model training job status
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10.3.4.3.1 Operation definition
The API Consumer uses this operation to query the AI/ML model training job status. The operation to query AI/ML model training job status is based on HTTP GET. Figure 10.3.4.3.1-1: Query AI/ML model training job status operation The service operation is as follows: 1) The API Consumer shall send an HTTP GET request to ...
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10.3.4.3.2 Referenced procedures
10.3.4.3.2.1 Query AI/ML model training job status procedure The query AI/ML model training job status operation illustrated in Figure 10.3.4.3.1-1 is based on the query AI/ML model training job status procedure defined in R1GAP [5].
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10.3.4.4 Notify AI/ML model training job status change
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10.3.4.4.1 Operation definition
The API Producer uses this operation to notify the status change of an AI/ML model training job. The operation to notify AI/ML model training job status change is based on HTTP POST. ETSI ETSI TS 104 231 V8.0.0 (2026-03) 134 Figure 10.3.4.4.1-1: Notify AI/ML model training job status change operation The service operat...
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10.3.4.4.2 Referenced procedures
10.3.4.4.2.1 Notify AI/ML model training job status change procedure The notify AI/ML model training job status change operation illustrated in Figure 10.3.4.4.1-1 is based on the notify AI/ML model training job status change procedure defined in R1GAP [5].
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10.3.5 Resources
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10.3.5.1 Overview
This clause defines the resource for the AI/ML model training API.
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10.3.5.2 Resource: "All AI/ML model training jobs"
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10.3.5.2.1 Description
The resource represents all AI/ML model training jobs created in the AI/ML model training API producer. The methods defined in clause 10.3.5.2.3 shall be supported by this resource.
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10.3.5.2.2 Resource Definition
Resource URI: {apiRoot}/ai-ml-model-training/<apiVersion>/training-jobs The resource URI variables supported by the resource is defined in Table 10.3.5.2.2-1. Table 10.3.5.2.2-1: Resource URI variables for the resource Name Definition apiRoot See clause 5.2. apiVersion See clause 10.3.2. ETSI ETSI TS 104 231 V8.0.0 (20...
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10.3.5.2.3 Resource Standard Methods
10.3.5.2.3.1 POST This method shall support the request data structures specified in Table 10.3.5.2.3.1-1 and the response data structures, and response codes specified in Table 10.3.5.2.3.1-2 and the HTTP headers specified in Table 10.3.5.2.3.1-3. Table 10.3.5.2.3.1-1: Data structures supported by the HTTP POST reques...
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10.3.5.2.4 Resource Custom Methods
None.
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10.3.5.3 Resource: "Individual AI/ML model training job"
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10.3.5.3.1 Description
The resource represents an individual AI/ML model training job created in the AI/ML model training API producer. The methods defined in clause 10.3.5.3.3 shall be supported by this resource.
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10.3.5.3.2 Resource Definition
Resource URI: {apiRoot}/ai-ml-model-training/<apiVersion>/training-jobs/{trainingJobId} The resource URI variables supported by the resource is defined in Table 10.3.5.3.2-1. Table 10.3.5.3.2-1: Resource URI variables for the resource Name Definition apiRoot See clause 5.2. apiVersion See clause 10.3.2. trainingJobId T...
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10.3.5.3.3 Resource Standard Methods
10.3.5.3.3.1 DELETE This method shall support the request data structures specified in Table 10.3.5.3.3.1-1 and the response data structures, and response codes specified in Table 10.3.5.3.3.1-2. Table 10.3.5.3.3.1-1: Data structures supported by the HTTP DELETE request body on this resource Data type P Cardinality Des...
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10.3.5.3.4 Resource Custom Methods
None.
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10.3.5.4 Resource: "Individual AI/ML model training job status"
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10.3.5.4.1 Description
The resource represents the status of an individual AI/ML model training job created in the Non-RT RIC. The methods defined in clause 10.3.5.4.3 shall be supported by this resource.
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10.3.5.4.2 Resource Definition
Resource URI: {apiRoot}/ai-ml-model-training/<apiVersion>/training-jobs/{trainingJobId}/status The resource URI variables supported by the resource is defined in Table 10.3.5.4.2-1. Table 10.3.5.4.2-1: Resource URI variables for the resource Name Definition apiRoot See clause 5.2. apiVersion See clause 10.3.2. training...
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10.3.5.4.3 Resource Standard Methods
10.3.5.4.3.1 GET This method shall support the request data structures specified in Table 10.3.5.4.3.1-1 and the response data structures, and response codes specified in Table 10.3.5.4.3.1-2. Table 10.3.5.4.3.1-1: Data structures supported by the HTTP GET request body on this resource Data type P Cardinality Descripti...
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10.3.5.4.4 Resource Custom Methods
None.
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10.3.6 Custom operation without associated resources
None.
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10.3.7 Notifications
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10.3.7.1 Notify training job status change
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10.3.7.1.1 Description
The notification informs the receiver about the updated status of an AI/ML model training job.
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10.3.7.1.2 Resource Definition
The Resource URI {notificationDestination} is a callback URI provided when creating an AI/ML model training job.
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10.3.7.1.3 Resource Standard Methods
10.3.7.1.3.1 POST This method shall support the request data structures specified in Table 10.3.7.1.3.1-1 and the response data structure and response codes specified in Table 10.3.7.1.3.1-2. Table 10.3.7.1.3.1-1: Data structures supported by the HTTP POST request body on this resource Data type P Cardinality Descripti...
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10.3.8 Data Model
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10.3.8.1 Structured data types
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10.3.8.1.1 Overview
The following clauses define the data types and attributes to be used by the AI/ML model training API. ETSI ETSI TS 104 231 V8.0.0 (2026-03) 138
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10.3.8.1.2 Data type: TrainingJobInfo
Table 10.3.8.1.2-1: Definition of type TrainingJobInfo Attribute Name Data type P Cardinality Description modelId ModelId M 1 The model identifier which contains model name, model version, and artifact version. See clause 10.1.8.1.3. modelLocation Uri O 0..1 Location of the AI/ML model. trainingDataset Uri O 0..1 Infor...
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10.3.8.2 Simple data types and enumerations
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10.3.8.2.1 Overview
The following clauses define simple data types and enumerations that can be referenced from data structure defined in the previous clauses.
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10.3.8.2.2 Simple data types
No simple data types are defined in the present document.
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10.3.8.2.3 Enumerations
No enumerations are defined in the present document..
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10.3.9 Error Handling
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10.3.9.1 General
For the AI/ML model training API, HTTP error responses shall be supported as specified in ETSI TS 129 501 [1]. Protocol errors and application errors specified in ETSI TS 129 500 [2], Table 5.2.7.2-1, shall be supported for an HTTP method if the corresponding HTTP status codes are specified as mandatory for that HTTP m...
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10.3.9.2 Protocol Errors
No specific protocol errors are defined in the present document.
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10.3.9.3 Application Errors
No additional application errors defined in the present document.
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10.4 AI/ML model deployment API
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10.4.1 Introduction
This API enables the API Consumer to request the deployment of an AI/ML model based on the AI/ML model deployment request service defined in R1GAP [5]. ETSI ETSI TS 104 231 V8.0.0 (2026-03) 139
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10.4.2 API version
For the AI/ML model deployment API as specified in the present document, the MAJOR version field shall be 1, the MINOR version field shall be 0 and the PATCH version field shall be 0 (see ETSI TS 129 501 [1] for a definition of the version fields). Consequently, the <apiVersion> URI path segment shall be set to "v1". T...
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10.4.3 Resource structure and methods
The request URIs used in HTTP requests from the API Consumer towards the API Producer shall have the resource URI structure as defined in clause 5.2. The <apiName> resource URI variable shall be " ai-ml-model-deployment". The <apiSpecificResourceUriPart> for each resource shall be set as described in clause 10.4.5. Fig...
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10.4.4 Service operations
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10.4.4.1 Request AI/ML model deployment
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10.4.4.1.1 Operation definition
The API Consumer uses this operation to request AI/ML model deployment. The operation to request AI/ML model deployment is based on HTTP POST. {apiRoot}/ai-ml-model-deployment/<apiVersion> /model-deployments /{modelDeploymentId} /status ETSI ETSI TS 104 231 V8.0.0 (2026-03) 140 Figure 10.4.4.1.1-1: Request AI/ML model ...
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10.4.4.1.2 Referenced procedures
10.4.4.1.2.1 Request AI/ML model deployment procedure The request AI/ML model deployment operation illustrated in Figure 10.4.4.1.1-1 is based on the request AI/ML model deployment procedure defined in R1GAP [5].
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10.4.4.2 Notify AI/ML model deployment status change
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10.4.4.2.1 Operation definition
The API Producer uses this operation to notify the change of an AI/ML model deployment status. The operation to notify AI/ML model deployment status change is based on HTTP POST. Figure 10.4.4.2.1-1: Notify AI/ML model deployment status change operation The service operation is as follows: 1) The API Producer shall sen...
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10.4.4.2.2 Referenced procedures
10.4.4.2.2.1 Notify AI/ML model deployment status change procedure The notify AI/ML model deployment status change operation illustrated in Figure 10.4.4.2.1-1 is based on the AI/ML model deployment procedure defined in R1GAP [5].
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10.4.5 Resources
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10.4.5.1 Overview
This clause defines the resource for the AI/ML model deployment API.
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10.4.5.2 Resource: "All AI/ML model deployment"
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10.4.5.2.1 Description
The resource represents all AI/ML model deployment in the Non-RT RIC. The methods defined in clause 10.4.5.2.3 shall be supported by this resource.
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10.4.5.2.2 Resource Definition
Resource URI: {apiRoot}/ai-ml-model-deployment/<apiVersion> The resource URI variables supported by the resource is defined in Table 10.4.5.2.2-1. Table 10.4.5.2.2-1: Resource URI variable for the resource Name Definition apiRoot See clause 5.2. apiVersion See clause 10.4.2.
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10.4.5.2.3 Resource Standard Methods
10.4.5.2.3.1 POST This method shall support the request data structures specified in Table 10.4.5.2.3.1-1 and the response data structures and response codes specified in Table 10.4.5.2.3.1-2. Table 10.4.5.2.3.1-1: Data structures supported by the HTTP POST Request Body on this resource Data type P Cardinality Descript...
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10.4.5.2.4 Resource Custom Methods
None.
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10.4.6 Custom operation without associated resources
None.
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10.4.7 Notifications
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10.4.7.1 Notify AI/ML model deployment status change
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10.4.7.1.1 Overview
The notification informs the receiver about the AI/ML model deployment status.
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10.4.7.1.2 Resource Definition
The Resource URI {notificationDestination} is a callback URI provided when requesting deployment of an AI/ML model.
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10.4.7.1.3 Resource Standard Methods
10.4.7.1.3.1 POST This method shall support the request data structures specified in Table 10.4.7.1.3.1-1 and the response data structure and response codes specified in Table 10.4.7.1.3.1-2. Table 10.4.7.1.3.1-1: Data structures supported by the HTTP POST request body on this resource Data type P Cardinality Descripti...
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10.4.8 Data Model
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10.4.8.1 Structured data types
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10.4.8.1.1 Overview
The following clauses define the structured data types and their attributes to be used by the AI/ML model deployment API.
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10.4.8.1.2 Data type: ModelDeploymentInformation
The ModelDeploymentInformation data type represents deployment information for an AI/ML model. It contains the attributes defined in Table 10.4.8.1.2-1. ETSI ETSI TS 104 231 V8.0.0 (2026-03) 143 Table 10.4.8.1.2-1: Definition of type ModelDeploymentInformation Attribute Name Data type P Cardinality Description modelId ...
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10.5 AI/ML model retrieve API
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10.5.1 Introduction
This API enables the API Consumer to request the retrieve of an AI/ML model based on the AI/ML model retrieve request service defined in R1GAP [5].
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10.5.2 API version
For the AI/ML model retrieve API as specified in the present document, the MAJOR version field shall be 1, the MINOR version field shall be 0 and the PATCH version field shall be 0 (see clause 4.3.1.1 of ETSI TS 129 501 [1] for a definition of the version fields). Consequently, the <apiVersion> URI path segment shall b...
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10.5.3 Resource structure and methods
The request URIs used in HTTP requests from the API Consumer towards the API Producer shall have the resource URI structure as defined in clause 5.2. The <apiName> resource URI variable shall be "ai-ml-model-retrieve". Figure 10.5.3-1 shows the overall resource URI structure defined for the AI/ML model retrieve API. Fi...
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1 Scope
The present document specifies the protocol conformance testing for testing a MCVideo Server for compliance to the Mission Critical Video (MCVideo) over LTE protocol requirements defined by 3GPP. The present document addresses only MCVideo Server-Server communication scenarios. It does not cover e.g. MCVideo Server-EPS...
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2 References
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2.1 Normative references
References are either specific (identified by date of publication and/or edition number or version number) or non-specific. For specific references, only the cited version applies. For non-specific references, the latest version of the referenced document (including any amendments) applies. Referenced documents which a...
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2.2 Informative references
References are either specific (identified by date of publication and/or edition number or version number) or non-specific. For specific references, only the cited version applies. For non-specific references, the latest version of the referenced document (including any amendments) applies. NOTE: While any hyperlinks i...
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3 Definitions of terms, symbols and abbreviations
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3.1 Terms
For the purposes of the present document, the terms given in ETSI TR 121 905 [i.1] (3GPP TR 21.905) and the following apply: NOTE: A term defined in the present document takes precedence over the definition of the same term, if any, in ETSI TR 121 905 [i.1] (3GPP TR 21.905). For the purpose of the present document, the...
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3.2 Symbols
Void.
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3.3 Abbreviations
For the purposes of the present document, the abbreviations given in ETSI TR 121 905 [i.1] (3GPP TR 21.905) and the following apply: NOTE: An abbreviation defined in the present document takes precedence over the definition of the same abbreviation, if any, in ETSI TR 121 905 [i.1] (3GPP TR 21.905). CSK Client-Server K...
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4 General
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4.1 Test methodology
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4.1.1 Testing of optional functions and procedures
Any function or procedure which is optional, may be subject to a conformance test if it is implemented in the MCVideo Server. A declaration by the MCVideo Server supplier (to use the Implementation Conformance Statement (ICS) proforma specified in ETSI TS 136 579-4 [2] (3GPP TS 36.579-4)) is used to determine whether a...
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4.1.2 Test interfaces and facilities
Detailed descriptions of the MCVideo test interfaces and special facilities for testing are provided in ETSI TS 136 509 [20] (3GPP TS 36.509).
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4.2 Implicit testing
For some 3GPP MCVideo protocol features conformance is not verified explicitly in the present document. This does not imply that correct functioning of these features is not essential, but that these are implicitly tested to a sufficient degree in tests which are not explicitly dedicated to test the feature.
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4.3 Repetition of tests
As a general rule, the test cases specified in the present document are highly reproducible and do not need to be repeated unless otherwise stated. 4.4 Handling of differences between conformance requirements in different releases of core specifications The conformance requirements which determine the scope of each tes...
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4.5 Reference conditions
The reference environments used by all signalling and protocol tests is specified in ETSI TS 136 579-1 [1] (3GPP TS 36.579-1). Where a test requires an environment that is different, this will be specified in the test itself. For all test cases in the present document unless specified otherwise the condition MCVIDEO ap...