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    How accurate mobile network planning can reduce a nationwide operator’s CAPEX by $2bn over 10 years

    Infovista, a global leader in network lifecycle automation (NLA), has released the findings of a report commissioned from Mobile Experts that shows how improved modelling precision in RAN planning and design optimisation can drive significant CAPEX savings for mobile operators by either increasing RAN capacity or deferring investment in additional spectrum and radio equipment.

    Mobile Experts calculates that a 1 dB improvement in RSRP modelling precision, could save a nationwide US mobile network approximately $2bn over a 10-year period through a reduction in the number of base stations and smalls cells deployed.

    The report, Accurate RAN Planning Saves Billions, calculates the impact of accuracy in sophisticated 3D modeling to predict the RSRP (reference signal received power) at each location. Mobile Experts’ modeling shows how, in a nationwide network, 1 dB higher precision in RSRP leads to roughly 0.4 bps/Hz overall improvement in spectral efficiency; with the same numbers of radios and the same antennas, this is the equivalent of a 24% increase of capacity.

    Joe Madden, founder and lead analyst at Mobile Experts says: “RAN planning tools have evolved into RAN optimization solutions that use a continuous cycle to deliver maximum return on the CAPEX invested. RAN Planning has also become instrumental to improving quality of experience, which minimizes churn. AI/ML-based, data-driven prediction engines are becoming the de-facto standard to deliver the accuracy required and ensure the optimal network design is arrived at.”

    “Our research clearly reveals the material impact accuracy in RAN planning and design optimization can have on capacity performance and CAPEX. In our years of experience with mobile radio networks, we have rarely seen any product that has such a big impact on the financial performance of the network. Any mobile network deployment will benefit from cloud-native, efficient, and integrated planning solutions, whether they are launching a brand new 5G network or preparing for new Network Slicing business offerings on the existing network,” Madden continues.

    The report outlines how improved accuracy in RAN planning can deliver more capacity and reduce CAPEX spending. While operators cannot get the full benefit of both improvements at the same time, they can choose a position that takes advantage of both benefits to some degree. Mobile Experts believes that most operators will choose to focus on improved RSRP precision for higher capacity, at least in the urban areas, in order to address peak capacity limitations that can be an issue in LTE and 5G networks and lead to dissatisfied customers. Better RAN planning, Mobile Experts argues, is an inexpensive way to boost capacity and Quality of Service (QoS), reducing customer churn that ties directly to lost revenue.

    Regis Lerbour, VP Product & R&D, RAN Engineering, Infovista adds: “The complexity, cost and scale of the 5G network is already a significant challenge, and only increasing. From deploying nationwide networks beyond initial city deployments to dynamically sharing LTE and NR spectrum, implementing 5G network slicing or building private mobile networks, 5G RAN planning must be built on both accurate real-world data today and predictive models of the future. This research by Mobile Experts clearly shows that there’s not just a business case for accurate RAN planning, there’s a business necessity for it. Infovista’s AI-powered RF planning solution, Planet is the driving force of innovation in this space, with recent breakthroughs leading to more accurate and efficient network planning and optimisation.”

    Rakuten Mobile Chief Technology Officer, Sharad Sriwastawa concludes: “Rakuten Mobile is implementing a cloud-native “on-demand” radio network planning solution with Infovista that allows our engineering teams to utilize advanced planning and design features devised to efficiently reduce the time and cost of network planning and deployment, through extensive automation”.

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