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Determining the execution environment for the UE Filterer, QoE Predictor, QoE Calculator and UE Intervention Selector will require some further analysis to weigh the Non-RT RIC and Near-RT RIC options. Data movement costs and interaction latency considerations will factor heavily into this analysis. Figure XXX provides a schematic that illustrates the data movement and other interfaces between the functional components described above.
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1 – Data Movement Between Functional Components
Both the UE Filterer and the QoE Calculator require high volume Per-UE Performance data for the serving cell: (UePerf) Current, Serving. In addition, the QoE Predictor requires the high volume fine grained Per-UE RF data for the serving and neighbor cells: (UeRf, CellPerf) Current. (See [REF] section 3.1.4 for a description of these data items.)
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The location of the training environment, co-located with the SMO/Non-RT RIC versus a central data lake, is a decision that depends mostly on business needs rather than technical considerations given that different business entities will decide differently how to weigh the relative cost of transporting massive amounts of data to a central data lake versus the benefit of having this data in such a data lake. This section will limit itself to describing the data needed during training and the high level training process envisioned.
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2 – Initial Training
Two of the data items required are quite voluminous: Per-UE RF and Per-UE Performance data. In Release B the desired training location will hence be a business decision that must be made evaluating the cost of transporting the data to a central data lake versus the benefits of having that data in a central data lake for initial training.
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In Release C we will go with approach “1”.
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3 – Reinforcement Training – Release C
Being unable to speak for all Service Providers on their business decisions, we will simply choose between the reasonable alternatives that which allows us to more fully exercise the named components in the O-RAN architecture. Namely, we will assume that initial training occurs in the SMO, co-located with the Non-RT RIC functionality. The SMO will collect the data across the O1 interface and make it available to the Model-in-training at the Non-RT RIC. The Near-RT RIC will report (UePerf) Current, Neighbor to the Non-RT RIC via O1. However this may not be achievable in the Release B timeframe given limitations in the available SMO functionality, and so we will take the following approach:
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