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Artificial intelligence and Telco networks: the evolution of the RAN Intelligent Controller
The integration of artificial intelligence into telecommunications networks, in particular through the RAN Intelligent Controller (RIC), represents an important step towards a more efficient, flexible and sustainable management of networks. The Open RAN approach and AI/ML technologies pave the way for new business models and advanced applications, transforming the network infrastructure to meet the needs of the future.
A rapidly evolving context
The evolution of next-generation networks will be strongly influenced by artificial intelligence, which will play a fundamental role in the context of 5G and subsequent technologies. These networks will not only improve the consumer experience, but they will also open up new opportunities for businesses. Using edge computing, it will be possible to implement innovative use cases, with native artificial intelligence distributed on a network, responding quickly to market and customer needs.
Today we are witnessing a rapid transition from a traditional, monolithic and closed architecture, based on unique suppliers, to completely open and disaggregated solutions. These new solutions are based on software modules that can communicate with each other, creating a more flexible and interoperable architecture.
A new business model
The Open RAN (Radio Access Network) approach is introducing a new business model in which RAN vendors, IT vendors, operators and system integrators collaborate to expand the potential of new applications in various markets, even outside of traditional telecommunications.
This new business model, called RAN-as-a-Service (RANaaS), allows customers to see the network as a platform from which they can request highly customized services or packages of use cases, thus being able to set up their own network in a flexible and modular way (network slicing).
The transition from RAN to O-RAN and the role of AI
An Open RAN network disaggregates the traditional RAN into open source and interoperable components, eliminating the binding dependence on the specific vendor, and introducing a new key element capable of conferring intelligence to the network: the RAN Intelligent Controller (RIC).
The RIC is the “operating system” of the RAN, which manages and coordinates the numerous network functions, now disaggregated on different hardware components, and also enables new ones thanks to the potential of AI/ML. The RIC introduces the ability to the network to perform functions directly guided by AI and machine learning (ML), allowing the creation of more flexible and efficient solutions. AI/ML models can not only be trained on the basis of large amounts of historical data, thus becoming very efficient in making the best decisions and predicting potentially dangerous situations, but they continue to be updated periodically, improving their efficiency, based on feedback from external sources or directly from end users. This allows the network to adapt quickly to the continuous changes to which it is subject, improving the final user experience.
The RAN Intelligent Controller can effectively improve network traffic management, detect anomalies, optimize the handover of mobile network cells, contribute to the efficiency of the network itself.
Use cases
The RAN Intelligent Controller (RIC) is not only a technological breakthrough, but a real innovation accelerator for mobile networks. Thanks to artificial intelligence, the RIC enables smart solutions to optimize network performance in real time, solving complex challenges such as traffic management and energy efficiency. Let's look at some of the most interesting use cases that are impacting different industries.
Traffic steering
A pioneering study introduced an intelligent handover framework, based on Deep Reinforcement Learning (DRL) to significantly improve network performance.
Improving traffic steering means improving the allocation of network resources to users who want to transmit data, reducing waste and waiting times. Currently, with the massive increase in devices connected to the network, optimizing the distribution of communication resources is a crucial issue, necessary to support innovative use cases that require high performance and avoid network congestion. An approach based on AI/ML algorithms that uses advanced architectures, has shown a 50% improvement in throughput and in the use of network resources.Energy Efficiency
Today, the need to reduce environmental impact, increasing sustainability and at the same time maintaining economic and operational efficiency, is more crucial than ever. The radio access network (RAN) represents an important part - 73% - of the energy consumption of telecommunications operators. To solve this problem, during the last Mobile World Congress, a solution based on two RAPPs (applications run by the RIC) was presented to reduce the energy consumption of the RAN. Using an LSTM-based ML model, the solution is able to predict future traffic and dynamically adjust cell capacity, reducing energy consumption by 20% per day.
The evolution of the RAN Intelligent Controller is transforming the way networks are managed, making them more intelligent and adaptable. With AI at its core, the RIC offers a dynamic approach to resource management, improving not only network performance, but also sustainability. This new era of telecommunications lays the foundation for a more resilient network ready to support emerging technologies.
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Net Reply is the Reply Group company that offers specialized solutions for Telco operators and large companies with distributed networks. Its mission is to provide innovative solutions in the transformation of networks and the OSS. Net Reply constantly invests in innovation and expertise in various key areas, including SDN & NFV, Cloud & NFVI, Network Data Centers, virtualized and automated networks, contextual communications, network data and analysis based on AI and ML approaches, as well as fixed and mobile network architectures, and Next Generation Networks (NGN).