How AI and Machine Learning in Open RAN reduce network complexity

New technologies, in addition to the complex distributed nature of most network environments, have complex network management. Ironically, to get around this complexity, some companies are integrating more technologies — including artificial intelligence and machine learning, or ML — within their network architectures.

Companies are not the only ones facing this predicament with network management. Mobile network operators (MNOs) also face complexity within their networks, including 5G network deployment. But mobile network operators are evaluating the latest technologies to simplify operations.

One of the ways in which operators try to reduce complexity is through an open wireless access network (Open RAN). With the Open RAN architecture, operators use non-proprietary equipment to improve interoperability, reduce costs, and increase programmability.

In a recent webinar, “How to Automate Predictive Processes AI/ML and Open RAN,” Brian Walsh — Director of Product Marketing at Parallel Wireless — discussed how MNOs can benefit from using artificial intelligence and machine learning in Open RAN, with cellular connectivity for complex processing. operations.

“Open RAN and new approaches in artificial intelligence and machine learning can help mobile operators improve operations in their networks, while reducing costs and complexity,” Walsh said.

Player Challenges

According to Walsh, MNOs face pressure to develop business operations to increase profits and differentiate themselves from competitors. On top of these challenges, new technologies like 5G have given end users higher expectations for the quality of service they can expect from service providers.

Some of these expectations include:

  • high productivity
  • a little latency
  • Network update
  • Quality and consistency

“Mobile operators must find new ways to increase their margin and improve network operational efficiencies through a more flexible and flexible service delivery environment, while reducing capital and operating expenses,” Walsh said.

Providing these network services increases costs and complexity, Walsh said. For example, the use of 5G and previous generations of cellular connectivity – such as 3G and 4G – to support access networks requires higher capacity for RANs and denser networks.

Network densification—the process of adding more cell towers to increase network capacity—can improve connectivity and reliability, among other benefits. However, the challenge of densification is that it is difficult for operators to obtain permission to create new cellular sites. But 5G networks are expected to be a hundred times denser than 3G networks, and densification is critical Deploying the 5G network and realizing its benefitsWalsh said.

AI and ML in Open RAN can enable self-improvement

Open RAN architectures enable operators to provide network self-optimization capabilities, which use automation to manage the network more efficiently. Walsh identified the following four components that help enhance network efficiency:

  • automation
  • Architectural Engineering
  • Applications
  • AI and ML

1. Automation

Automate network tasks Walsh said touchless provisioning could simplify network operations and management. Operators use automation to increase the size of their operations without hiring more employees.

2. Architecture

One of the developments in the Open RAN architecture is the integration of ML frameworks. For example, the Smart RAN Controller allows operators to programmatically control RAN in and out of real time.

3. Applications

Open RAN applications support ML models, which automate the network and make data-driven decisions. According to Walsh, either external organizations or MNOs can develop Open RAN applications.

4. AI and ML

Predictive models of artificial intelligence and machine learning use algorithms to process data by analyzing past and current data events and finding patterns. Walsh said that implementing these tools and automation within RAN architectures helps eliminate human error and is a major advance in the networking industry.

Unlock RAN ​​Deployment Challenges

Ideally, according to Walsh, the combination of the above four components would result in the creation of self-optimizing intelligent networks.

But doubts about Open RAN remain, despite the use cases. Similar to artificial intelligence and machine learning, Open RAN is a recent development in the networking world, and MNOs are hesitant to implement it. a study From mobile world live, In partnership with Aspire Technology, it surveyed 370 operators from various industries and found that the operators are split on Open RAN deployment.

Much of this reluctance stems from the fact that operators are not familiar with the technology. An estimated 57% of respondents said they need to know more about Open RAN or are not familiar with the technology at all. Research from Eightfold AI confirms this; According to a study drawn from a data set of 500,000 communications employee profiles, 33% of network engineer and operations roles are not equipped to deliver innovative offerings. Some of these offerings include emerging network technology trends, such as 5G and Open RAN.

The future of artificial intelligence and machine learning in Open RAN 5G

Experts expect that The open RAN market will thrive As technology evolves, skills and knowledge gaps are likely to shrink during this time frame. The majority of respondents said Mobile World Live They believe that Open RAN requires another two to five years of maturity before large-scale deployments can occur. More vendors may also have services to integrate Open RAN 5G with AI and ML by then.

Parallel Wireless, for example, currently provides an Open RAN cloud architecture that supports 5G and earlier cellular generations, along with AI and ML frameworks, to help operators modernize their networks. However, Parallel Wireless isn’t the only vendor that has made headway in this area. Other players in the industry are beginning to make progress in automating 5G networks that support open RAN.

In February 2022, Anuta Networks unveiled ATOM, its standalone 5G network configured with Open RAN as a service. According to Anuta, ATOM includes predictive analysis tools for AI and ML, among other features. In late 2021, Ericsson announced the launch intelligent automation platforma service that adds automation capabilities to both traditional 4G and 5G RAN and RAN networks – including Open RAN.

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