Power of Automation in Open RAN
The rapid advancements in Open RAN have opened many gates for the operators to deploy the technology which comes with more flexibility and agility to disintegrate the traditional RAN which is proprietary and has vendor-specific characteristics.
With the adoption of the Open RAN, the disaggregation of the coupled radio, hardware, and software has presented integration challenges. But, the real question is that how can one integrate both software and hardware from different vendors and be able to automate the software upgrades?
To handle the vendor diversity, the Open RAN networks rely on automation which addresses these challenges and provides the mobile network operators the real benefits of ORAN like the flexibility of choice, cost savings, scalability, ease of management and upgradeability, etc.
Without automation, the time required to complete the validations will be a factor in the number of possible combinations of different RU, DU, and CUs.
But now the question comes, how can one enable automation in Open RAN?
Well, the answer is rather simple. The Cloud-native Open RAN solution brings important automation tools like the Zero-Touch Provisioning (ZTP), Artificial Intelligence, Machine Learning, and Continuous Integration/Continuous Delivery (CI/CD), coupled with Analytics to enable this automation in the network deployment.
Let’s first start with what exactly is ZTP.
ZTP- Zero Touch Provisioning
The ZTP is brought into action once the infrastructure for the network environment is set up with a software-defined approach. To provide the service or bring a radio site automatically with no manual intervention is what ZTP is all about.
In a nutshell, a mobile operator does not have to perform any manual tasks to configure the cell sites because with ZTP these sites can be configured instantly and automatically.
Once these are configured, the Continuous Integration and Continuous Development (CI/CD) in O-RAN comes into the picture to automate any updates and reduce any manual labor involved on-site or in the data center resulting in cost reduction for the MNOs.
Continuous Integration/ Continuous Development (CI/CD)
The RAN is the most time-sensitive and transaction-intensive area of the network and any performance issues will create calamity on the user experience. Even though it needs to adopt a data center approach to develop, run and optimize software, the O-RAN brings new challenges in the complexity of integrations and software upgrades between different vendors.
CI/CD in telecommunications is the set of practice that enables how software, in our case, RAN software, gets delivered. Continuous Integration is the execution of merging all developers to shared mainline several times a day.
The actual development of a suite of interoperability tests i.e increased validation and integration amongst Open RAN vendors is the main challenge. A unique set of tests are needed to standardize the certification of software, whether it is hosted on bare-metal infrastructure or on a cloud.
The integration, software upgrades, and lifecycle management of these disaggregated software components running on COTS hardware are enabling a new testing model, where software from the different groups within an organization is not tested in silos, but rather under an overall CI/CD environment.
Therefore as the O-RAN ecosystem evolves, the number of software upgrades will also increase and so will the need to include these upgrades in the CI/CD environment.
The DevOps need to implement a set of new automation to be used across the group for monitoring and testing the application and keeping it secure via the CI/CD. To enable fast changes to the software and be able to deliver the end-user needs the CI/CD in O-RAN helps to meet these requirements.
“ Only the Telecos that harness the full potential of Artificial Intelligence tools will thrive”
Artificial Intelligence & Machine learning
Telcos plan to use AI to automate network operations and enhance them to meet the required user experience.
To manage secure network operation, AI coupled with ML provides intelligence and response to take different actions on the network – for example, scaling. This guarantees the quality of network performance and its operational efficiency resulting in harnessing the Open RAN’s flexibility.
To optimize these networks, AI analyses the data and classifies them such that it then recognizes the pattern or abnormality to predict the behavior. With the evolution of time, Machine Learning will evolve and become better at predicting and helping AI to make real-time network decisions.
The openness in the Open-RAN will complement AI when it covers the data of different use cases that include the data from different vendors along with the overall network and just the components of RAN.
Therefore, in brief, the AI/ML algorithms will be taking charge of forecasting parameters, detecting abnormalities, predicting failures, and classifying components into groups such that the ability to predict the future with some accuracy can be enabled.
Analytics
A tool that gives insight into what’s going on in the network by providing a visual representation of patterns or anomalies and how they affect the subscriber experience is what Analytics is all about.
Improving the network performance for a better subscriber experience is what Analytics stands for. It also reviews the AI data and sees reports on how ML is improving the network such that this network and subscriber data can produce hourly and daily reports on behavioral and network patterns.
Cloudification with microservices and containers
Cloudification doesn’t convey running the RAN services from the cloud. It means virtualizing RAN services via cloud-native tools i.e the microservices and containers. These tools are the fundamental blocks of the Open RAN. To optimize the RAN function’s performance, software implementation went from monolithic, self-contained applications running on dedicated servers to a new model that eventually evolved to microservices. A microservice is the decomposition of an application into a multitude of separate parts, each one of them running in a lightweight “container”-like environment. This allows developers to change only specific microservices as needed. These microservices can be deployed, upgraded, and scaled independently in the RAN application via an automated system. Since the architecture of the microservices allows MNOs to continuously innovate the agile DevOps model, it also pushes out the upgrades to as many sites as are needed.
Summary
The key element to power innovation in the Open RAN are the “Automation Tools” required for the MNOs to get a flexible, elastic, and efficient Open RAN solution. The automation in Open RAN configuration with ZTP, AI/ML, CI/CD, and Analytics will help MNOs to avoid vendor lock-in and provide better resource utilization.
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