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New Infovista report identifies significant CAPEX savings
Mon, 11th Jul 2022
FYI, this story is more than a year old

A new report by Infovista has found that making modelling more precise in RAN planning and designing can foster major CAPEX savings for mobile operators.

Mobile Experts commissioned the network lifecycle automation (NLA) company's report and found that increasing RAN capacity or deferring investment in additional spectrum and radio equipment could offer greater cost-efficiency.

Mobile Experts calculates that by making RSRP (reference signal received power) modelling 1 dB more precise, a nationwide US mobile network could save roughly $2 billion over a 10-year period by reducing how many base stations and small cells are deployed.

The report, titled Accurate RAN Planning Saves Billions, measures the impact of accuracy in sophisticated 3D modelling to predict the RSRP at each location.

Mobile Experts' modelling indicates that making RSRP 1 dB more precise in a nationwide network will result in approximately 0.4 bps/Hz overall improvement in spectral efficiency.

Further, with the same quantity of radios and the same antennas, this equals a 24% increase in capacity.

“RAN planning tools have evolved into RAN optimisation solutions that use a continuous cycle to deliver maximum return on the CAPEX invested,” Mobile Experts founder and lead analyst Joe Madden says.

“RAN Planning has also become instrumental to improving quality of experience, which minimises 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 optimisation 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.

In addition, the report notes that while operators will be unable to get the full advantage of both reduced CAPEX spending and greater capacity simultaneously, they will be able to choose a position that allows them to have both benefits to some degree.

Mobile Experts believes that many operators will elect to focus on making RSRP more precise to foster greater capacity, at least in urban areas, to address peak capacity limitations that can be a problem in LTE and 5G networks and cause customers to be dissatisfied.

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

Mobile Experts also says improving RAN planning is an inexpensive way to generate more capacity and Quality of Service, minimising customer churn that leads to revenue loss.

“The complexity, cost and scale of the 5G network is already a significant challenge, and only increasing,” Infovista RAN Engineering research and development and product vice president Regis Lerbour says.

“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.