{"id":33469,"date":"2022-04-22T11:26:34","date_gmt":"2022-04-22T08:26:34","guid":{"rendered":"https:\/\/saudishopper.com.sa\/en\/?p=33469"},"modified":"2026-03-28T00:49:56","modified_gmt":"2026-03-27T21:49:56","slug":"closing-the-loop-on-5g-network-automation","status":"publish","type":"post","link":"https:\/\/saudishopper.com.sa\/en\/closing-the-loop-on-5g-network-automation\/","title":{"rendered":"Closing the loop on 5G network automation"},"content":{"rendered":"\n

By Dimitris Mavrakis, ABI Research<\/p>\n\n\n\n

Unlike previous cellular generations, 5G will be at the heart of the digital transformation of many industry verticals and will help network operators address ever-increasing data traffic and various connectivity requirements.<\/p>\n\n\n\n

Current 5G networks are already achieving Gigabits per Second (Gbps) speeds for many users and leading Tier One mobile operators to report that 5G sites carry more than 200 Terabytes (TB) every single day, something we could not dream of 5 years ago when 4G was still dominant. At that time, mobile operators were selling subscriptions of 1 Gigabyte (GB)\/month and were reporting that their networks could handle anything users consumed below this 1 GB\/month threshold. In contrast, 5G allows individual users to consume up to 1 TB\/day today. This is a monumental achievement by the cellular industry in only a few years\u2019 time.<\/p>\n\n\n\n

Nevertheless, this increase in traffic, coupled with the number of devices also increasing, means that networks are becoming more difficult to manage, causing Operations and Maintenance (O&M) costs to inflate network Operational Expenditure (OPEX) considerably. Future 5G service prospects, predominantly in the enterprise domain, will accentuate this, especially when mobile operators aim to introduce Service-Level Agreements (SLAs) for enterprise use cases. At the same time, networks are becoming more complex, so mobile operators will have to manage the coexisting 2G\/3G\/4G\/5G networks at the same time for a long time.<\/p>\n\n\n\n

The conventional way to handle network automation relies on a team of engineers using mathematical modeling and optimization to set up rules and predetermined threshold instructions manually, where system design and network performance are purely based on human observations and experiences. The implementation of Artificial Intelligence (AI)\/Machine Learning (ML) technologies offers a great opportunity to introduce more simplified and proactive network management skills; by improving the cognitive capability of Radio Access Network (RAN) infrastructure, the AI\/ML-based automation mechanism, including model training and inferring, can help network operators forecast the possible network risks and faults for better network O&M and user-service assurance.<\/p>\n\n\n\n

\u201cNetwork Intelligence\u201d is a main topic of MWC22<\/p>\n\n\n\n

Network intelligence was a hot topic at MWC22. The O-RAN Alliance also argued that network intelligence and automation are its goals. But the true implementation of these open networks will likely take many years to materialize, as new entrants need to develop their infrastructure to reach the levels of Tier One vendors, namely Ericsson, Huawei, Nokia, Samsung, and ZTE. Moreover, 99% of today\u2019s 5G networks are brownfield, meaning they are already deployed and serving customers. Therefore, many mainstream vendors announced their own intelligence engines to offer these new capabilities, while allowing existing networks to retrofit them to enjoy similar benefits.<\/p>\n\n\n\n

For example, Huawei launched the IntelligentRAN, a new wireless network architecture that is an implementation of its Autonomous Driving Network concept to automate mobile networks to achieve the following goals:<\/p>\n\n\n\n