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radisys.com 19 Radisys Series — Who Disaggregated My RAN? eBook many xApps in the Near Real-time RIC to solve these problems, serve those uses, and delivery much better QoE (Quality of Experience) to the mobile subscribers. Operators are moving to making the network more intelligent, adding more sophisticated algorithms into the controllers and enabling multiple use cases as seen in the figure above. Handover optimization, load balancing, and other use cases can be handled by algorithms in the Near Real-time RIC and adds automation to the network. The Near Real-time RIC specification developed within the O-RAN Alliance is now available for download. The introduction of RIC fundamentally alters the way RAN is managed and optimized by the operators. This also impacts the way RAN base stations (CU and DU) are delivered as products by vendors. In addition, it opens the arena to a completely new set of players who can focus on the problem solving at a network level with clever algorithms. AI/ML and Support for xApps In this new architecture, AI and ML are algorithmic in nature and in the Real-time Intelligent Controller platform, they support the collection of all of the underlying network nodes in the RAN. This creates a database in the platform that will support multiple applications and it is called xApps. xApps can be used for a specific use case, a specific optimization, or a specific feature. We are all familiar with App Stores for Android and iOS devices. We download and use different apps for a variety of purposes. The xApps will be hosted on the RIC, and in a not-so-distant future, there will be an "xApps Store" for the mobile network. Multiple vendors will submit their own algorithms for the store. For example, a company could develop an app that is focused just on load balancing or just on mobility control. Mobile operators will be able to select which apps they want to use in the RIC. 5G networks with this intelligence layer added with the RIC should perform much better and more dynamically react to the changing conditions of the network. The Non Real-time RIC Looking one layer above the Near Real-time RIC is the Non Real-time RIC. The Non Real-time RIC enables network optimization and provides policy control. It ingests and processes a lot of enrichment information – data that is pulled from management entities (SMOs), network functions and other sources. This valuable data from the network can be huge in volume. This data can be processed further with AI/ML algorithms to deduce insights and actions. Policy management for fulfilling different services is another key aspect of this node. Policies are communicated to the Near Real-time RIC via the A1 interface. The latency for the Non Real-time RIC is greater than a second due to the sheer amount of processing required.

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