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The Promise of Zero-Regret Network Investment Decisions

The Promise of Zero-Regret Network Investment Decisions

5G networks are the backbone of our connected lives. Since the first 5G launches in 2018-2019, the number of Internet of Things (IoT) devices has increased exponentially, from smartphones and tablets to heavy assets and buildings. Higher speeds and bandwidth have created myriad new possibilities and innovations. But that demand has come with a cost: the sheer amount of data generated by billions of connected devices, and its impact on operators’ investment decisions. 

 

Telecom companies today must expand their networks rapidly to meet the growing use of data. They’re also challenged to optimize network efficiency and performance while finding ways to monetize their latest 5G investments. Considering the accelerating use of mobile devices, and the escalated amount of data they generate, the speed and accuracy of operators’ CapEx and other investment decisions are more critical than ever. The need of the hour is simple: figuring out how to make more-informed decisions that maximize the ROI of their network expansion.

 

Zero-Regret Investment Strategy for Telecommunications

Consider the task of determining the optimal location for new towers or fiber. Experts conduct extensive surveys and feasibility studies to identify potential sites that maximize coverage. They then analyze geographical information, population density, existing infrastructure and other data in an attempt to meet current and future demand. This complex and often manual process can take several months to a year. 

 

What if that analysis could be completed within a few days, and with comparable or even greater accuracy?

 

This challenge is an ideal use case for AI and digital twins. With AI algorithms, operators can analyze massive datasets to identify patterns and predict demand that help decision makers prioritize tower locations with the most significant potential impact.

 

Digital twins, or virtual models of the physical network, then allow operators to simulate different deployment and optimization scenarios to assess the feasibility of each with real-time data. The model helps operators answer critical questions such as:

 

  1. How should they expand their network to allocate resources most efficiently and with the ideal mix of technologies?
  2. What are the best locations to lay fiber?
  3. Where are the optimal locations for new towers? 
  4. How can they boost the capacity of existing equipment rather than invest in entirely new assets?
  5. How will the new network allow increasing loads to be managed and balanced in the future?

 

Together, AI and digital twins offer an ideal approach to network planning and optimization that maximizes the coverage and cost-effectiveness of a rollout plan. The combination of technologies also offers network owners unprecedented precision and insights, essentially providing a zero-regret investment strategy. 

 

Practical Yet Powerful: AI Network Planner

Equipment placement is critical to cost savings in the telecommunications industry. Sand Technologies’ AI Network Planner, which will be showcased at MWC-Las Vegas, provides CTOs with a detailed investment roadmap, optimizing the network rollout strategy at the tower-by-tower, street-by-street and building-by-building level.

 

With an ML and algorithm-based system, telecom companies can use satellite images and LiDAR data, information that has existed for years but often been too large or complex to analyze. Algorithms find the highest-impact locations for network improvements at the lowest possible price, and they can help operators develop comprehensive network-building strategies in a matter of days. 

 

AI Network Planner also provides detailed insights into customer demographics, competitor coverage and the optimal network expansion configurations using machine learning, network graph analytics, geospatial analytic, and cash-flow modeling. These insights enable telecoms to optimize their CapEx investments for maximum reach. Deployments by telecom leaders around the world have shown that these data-driven insights can improve IRR by up to 10% and reduce cost-to-build by up to 50%.

 

How AI Network Planner Works

Telecom companies can use this tool in multiple ways. In the example below, the model is helping to identify profitable uptake areas. Each colored dot represents an existing tower. The colors indicate tower profitability (red is no or low profit, and green is high profit). By hovering over a tower’s icon, operators can quickly see its long-term profitability.

 

 

 

Figure 1: Existing towers with profitability

 

When used at scale, this tool makes advantageous investment opportunities obvious. In the image below, the operator has overlaid tower profitability with various fiber rollout plans. After zooming-in to one potential are for investment, it becomes clear that there are two highly profitable towers adjacent to a low-profit fiber rollout plan. 

Figure 2: Tower profitability overlaid with coverage areas.

 

The model provides tower configurations that allow potential uptake in the red area - without adding fiber. This powerful insight allows the telecom to optimize the two towers for maximum revenue rather than invest in the more-expensive option of laying new fiber in what would otherwise be a low-profit area.

 

Network Digital Twin Planner 

Digital twins can simulate real-world operations, allowing scenario testing that leads to more-informed decisions, ultimately reducing the number of miscues and poor investments. The Network Digital Twin uses AI and data modeling to provide strategic decision-makers with scalable network simulations.

 

The Network Digital Twin can model complex network scenarios, leveraging various integrated data sources. The underlying technology uncovers patterns, anomalies and opportunities for growth. It also optimizes network planning, increases ROI and helps plan for the future using various scenarios for long-term monetization.

 

By using a Network Digital Twin, RAN planners, operators and analysts can run real-time experiments, optimize network configurations and adapt to demand fluctuations before making major investment decisions.

 

The model also increases decision-making efficiency and provides a single source of truth, delivering a comprehensive set of roadmaps to guide fiber rollouts, capture value and enable the most strategic network expansion possible.

 

How Network Digital Twin Works

The image below shows the results of an operator analyzing its network in a specific area. The dark red circles represent signal demand, while the right side shows the existing towers. Each of the green towers, meanwhile, represents an opportunity to make adjustments that could significantly improve network performance and the customer experience. In fact, the underlying technology can even be used to optimize power based on demand, reducing consumption and contributing to the operator’s sustainability goals.

 

Figure 3: Screenshots from the Network Digital Planner

 

In the example above, 504 possible configuration adjustments, if implemented, are projected to achieve the following improvements:

 

  • 5.4% improvement in demand
  • 17.82% customer satisfaction improvement
  • 27.6% reduction in energy consumption

 

Planning network growth is a strategic exercise; it determines the carrier’s future direction. As customer needs grow, so too does the operator’s need to optimize or expand its infrastructure. By using a Network Digital Twin, communication service providers (CSPs) can model the available options and the predicted network impact before making a single investment decision, saving both time and money.

 

Two Success Stories Using the Technology

Applying AI with digital twins isn’t just a theoretical use case. The pairing has been used successfully around the world. For one client, the model enabled operators to map infrastructure gaps and optimize their network deployment. Digital twins enabled them to identify the most-effective way to deliver broadband access, from 4G to 5G to satellite internet. Then, by layering analytics, the operator could build granular yet accurate business cases for each access strategy, down to the street and even building level.

 

In another example, AI identified a strategic deployment plan for a multi-billion dollar telecommunications company. With customers’ expectations soaring and technology advancing at an unprecedented rate, the challenge was multifaceted: How to modernize and scale without sacrificing quality or efficiency? By harnessing AI, the operator determined that it was most effective to prioritize large-scale fiber rollouts. The decision was right: the operator realized $4 billion in value and identified four million new homes for potential coverage in a national fiber initiative.

 

Sand Technologies at MWC Vegas 2024 

As the world demands more connectivity and capacity, network operators have an opportunity to evolve and build networks more intelligently and profitably. Visit Sand Technologies in booth 921 at MWC-Las Vegas to see some of the AI and data-driven solutions that telecom leaders have used to optimize their operations, inform their buildout strategies and maximize their ROI from network investments.