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-.. This work is licensed under a Creative Commons Attribution 4.0
- International License. http://creativecommons.org/licenses/by/4.0
-
-.. contents::
- :depth: 3
-..
-.. _docs_5G_oof_pci:
-
-
-OOF-PCI
---------
-
-Description
-~~~~~~~~~~~
-
-The 5G OOF-PCI use case is an implementation of a SON (Self-Organizing Networks) algorithm
-for Physical Cell ID (PCI) optimization and the centralized Automatic Neighbor Relations
-(ANR) function (blacklisting a neighbor for handovers) in a 4G/5G network using the ONAP
-Optimization Framework (OOF). This use case began with the implementation of PCI
-optimization in Casablanca. In Dublin release, the SON-Handler MS was onboarded as a
-micro-service in DCAE. Enhancements were made to Policy and SDN-C components. Further
-details of Dublin release scope and impacts for this use case are described in:
-https://docs.onap.org/en/dublin/submodules/integration.git/docs/docs_5G_oof_pci.html#docs-5g-oof-pci
-
-.. image:: https://wiki.onap.org/download/attachments/81401601/image2020-3-26_5-40-10.png?version=1&modificationDate=1585219211000&api=v2
- :alt: OOF-PCI
-
-In Frankfurt release, the following are the main enhancements:
-
-- Introduction of Control Loop Coordination functionality, wherein a second control loop execution is
- denied by Policy component when another control loop is in progress.
-- Introduction of adaptive SON, wherein a set of cells whose PCI values are fixed (i.e., cannot be changed
- during PCI optimization) are considered during the PCI optimization.
-- In addition, the first step towards O-RAN alignment is being taken with SDN-C (R) being able to receive a DMaaP
- message containing configuration updates (which would be triggered when a neighbor-list-change occurs in the RAN
- and is communicated to ONAP over VES). Details of this implementation is available at:
- https://wiki.onap.org/display/DW/CM+Notification+Support+in+ONAP
-
-
-In Guilin release, the main enhancement was related to taking the first steps for enabling Machine-Learning (ML) based
-SON functionality. Training is assumed to be done offline, and the ML model is then onboarded to ONAP as part
-of OOF. The ML model provides additional inputs (based on the handover PM data) to the optimizer about cells
-whose PCI values should not be modified during the PCI optimization process. To be able to do this, the ML model
-that is part of OOF fetches historical PM data from a data base/data lake using the DES micro-service (in DCAE)
-APIs. This is a new capability introduced in OOF which can be extended further for other scenarios. To be backward
-compatible, the functionality in OOF to invoke the ML model for additional inputs before PCI optimization is
-performed is configurable.
-
-The end-to-end setup for the use case requires a Config DB which stores the cell related details of the RAN. This is
-updated by SDN-C (R), and is accessed by SON-Handler MS and OOF for fetching, e.g., neighbor list, PNF id, etc.
-
-The Config DB implementation is available at:
-https://github.com/onap-oof-pci-poc/sdnc/tree/master/ConfigDB/Dublin
-
-Swagger JSON API documentation can be found at:
-https://github.com/onap-oof-pci-poc/sdnc/blob/master/ConfigDB/Dublin/SDNC_ConfigDB_API_v3.0.0.json
-
-As part of this use case work, a RAN Simulator providing a simulated Radio Access Network (RAN) with a number of
-netconf servers simulating PNF elements has been implemented. The functionality of the RAN Simulator includes:
-
-- Generation of neighbor-list-update messages
-- Generation of alarms for PCI collision/confusion and
-- Generation of handover metrics for different neighbor pairs (for the ANR use case).
-
-All above functionality are enabled using a simple UI.
-All details regarding the use case for Guilin can be found here:
-https://wiki.onap.org/display/DW/R7+OOF+SON+Use+Case
-
-All details regarding the use case for Frankfurt can be found here:
-https://wiki.onap.org/display/DW/OOF+%28SON%29+in+R5+El+Alto%2C+OOF+%28SON%29+in+R6+Frankfurt
-
-The main use case page is:
-https://wiki.onap.org/display/DW/5G+-+OOF+%28ONAP+Optimization+Framework%29+and+PCI+%28Physical+Cell+ID%29+Optimization
-
-How to Use
-~~~~~~~~~~
-
-The OOF-PCI use case is set up in the Rutgers University (Winlab) ONAP Wireless Lab (OWL). For details, please see:
-https://wiki.onap.org/pages/viewpage.action?pageId=45298557.
-
-This page includes instructions for access to the lab. Setup and testing is done manually up to now.
-
-For all instructions about installing the components, please see:
-
-- Frankfurt Installation: https://wiki.onap.org/display/DW/Demo+setup+steps+for+Frankfurt
-- Guilin Installation: https://wiki.onap.org/display/DW/SON+use+case+demo+setup+steps+for+Guilin
-- Son-Handler installation: https://docs.onap.org/projects/onap-dcaegen2/en/frankfurt/sections/services/son-handler/installation.html?highlight=dcaegen2
-
-Test Status and Plans
-~~~~~~~~~~~~~~~~~~~~~
-
-For Guilin release, the enhancements described above were implemented. OOF was enhanced with invoking the onboarded
-ML model for additional inputs on cells with fixed PCI values during the optimization.
-
-To see information about test plans, please see https://wiki.onap.org/display/DW/Integration+Test+for+Guilin.
-
-Known Issues and Resolutions
-~~~~~~~~~~~~~~~~~~~~~~~~~~~~
-
-(a) It is intended to have the RAN Simulator support sufficient Honeycomb netconf server instances to simulate 2000 cells.
- However, this number may be lower if there are hardware limitatons.
-(b) For Control Loop Co-ordination, the denial of a second Control Loop based on Target Lock (i.e., when a second Control
- Loop tries to operate on the same target (in this case, a PNF) is successfully tested.
- The CLC is also applied at Control Loop level only.
-(c) There are some limitations in the DES APIs with respect to supporting generic queries. These will be addressed in
- Honolulu release and beyond.
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