Operators can save billions with better RAN planning – white paper
- Telcos can save capex worth billions if they plan network deployments more precisely, a new white paper suggests
- Improved modelling that covers planning and design optimisation can decrease the number of base stations and small cells deployed
- Accurate RAN planning can boost efficiency and increase capacity by 24%, according to the research
Telcos can save billions of dollars if they embrace smarter and more accurate planning methods when deploying new networks, according to a new white paper by analyst firm Mobile Experts.
The research, which was commissioned by Infovista and is available here, estimated that savings from mobile network planning could reach as much as $2bn in terms of capital expenditure (capex) of a nationwide operator over a 10-year period. The reduction is possible through improved modelling precision in radio access network (RAN) planning and design optimisation, which results in fewer base stations and small cells being deployed in a network rollout, noted the author of the report and founder of Mobile Experts, Joe Madden.
In fact, the report suggests that just 1 decibel (dB) higher precision in the 3D modelling process improves the spectral efficiency and increases capacity by 24%, using the same number of radios and antennas. As a result, the report continues, mobile operators can either increase RAN capacity or defer investment in additional spectrum and radio equipment. Mobile Experts expects most telcos to focus on improved precision for higher capacity in urban areas to address limitations in LTE and 5G networks that can lead to dissatisfaction in customers.
According to Madden, better RAN planning is now “much more than a one-time, best-effort decision to place the radio sites in the right locations” and acts as “an inexpensive way to boost capacity and quality of service, reducing customer churn that ties directly to lost revenue”.
Madden argues that any mobile network deployment – whether it’s a brand new 5G network or preparing for new network slicing offerings on an existing one – would benefit from “cloud-native, efficient and integrated planning solutions”.
Going into details of the qualities required for effective RAN planning, Madden highlighted the role of artificial intelligence (AI)/machine learning (ML)-based data-driven prediction engines, which are now becoming “the de-facto standard to deliver the accuracy required and ensure the optimal network design is arrived at”.
He noted that the optimal planning tool needs to provide efficient workflows and faster computational cycles; to be data-driven and to leverage multiple input data sources; to be integrated into network lifecycle automation processes, such as testing and assurance; and to be cloud native so that it enables new capabilities, such as nationwide predictions at any resolution and faster computation times.
The report also provides an example in the form of Japanese operator Rakuten, which uses a cloud-native RAN planning solution by Infovista to reduce the time and cost of network planning and deployment.
Mobile Experts expects that more operators will increase their investments in RAN planning and optimisation tools, “as the operations team and the CFO can both agree that this is an effective way to guide the investment in the field.”
- Yanitsa Boyadzhieva, Deputy Editor, TelecomTV
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