The Role of Private Wireless Networks in the Energy Industry

The energy and utility sectors occupy a unique position in the global landscape, serving as the bedrock of national infrastructures while demanding unparalleled levels of communication reliability, security, and uptime. These industries, encompassing everything from electricity and gas distribution to renewable energy generation, are characterized by critical requirements that necessitate robust communication networks. Amidst this backdrop, the deployment of private wireless networks has emerged as an essential element, reshaping how energy operations are conducted and monitored.

Navigating the Landscape of Energy Communication

Unlike many other industries, energy and utility companies have long cultivated sophisticated network infrastructure and internal expertise. With a historical focus on low latency demands and stringent reliability requirements, these sectors have often demanded 99.9999% uptime (up to six or seven nines of reliability).

Their networks can endure life cycles of 20-30 years, covering large geographical areas and even entire nations. These networks are designed to be resilient, ensuring operational continuity even in the face of adverse conditions.

The multifaceted nature of these industries, coupled with the necessity for real-time communication, has prompted the development of proprietary network infrastructures tailored to control and monitor assets, sites, and employees. Energy and utility companies are acutely aware of the need for low latency, making voice and data communication systems crucial. These networks are designed with an emphasis on redundancy, security, and resilience, with cybersecurity concerns taking center stage.

The Era of Convergence: Private Networks for Energy and Utilities

In recent years, a confluence of factors has led to the convergence of wireless networks and the energy and utility sectors. This convergence is marked by two critical shifts:

Standardization of Wireless Technologies: With the widespread adoption of 4G and 5G cellular technologies, wireless networks have become more accessible beyond traditional mobile network operators (MNOs). Energy and utility companies are increasingly inclined to establish their own private networks, giving them greater control and ownership over their communication infrastructure.
Transformation of Energy Assets: The energy landscape is undergoing a transformative shift driven by decentralization, data-driven operations, and interconnectedness. This transformation necessitates enhanced connectivity to enable real-time monitoring, control, and data collection across distributed assets.

The Value of Private Networks for Energy and Utilities

The growing demand for private networks in the energy and utility sectors is driven by a series of overarching changes, each elevating the need for enhanced connectivity, control, and information flow:

Infrastructure Modernization: Modernizing aging infrastructure with private networks facilitates real-time data collection, control, and flexibility. This allows for efficient asset management, automation, and streamlined repair and restoration processes, reducing downtime and enhancing resource allocation.
Employee Safety and Productivity: In hazardous environments, private networks significantly improve the safety of utility workers. They offer robust voice and video communication capabilities, ensuring seamless communication even in remote or challenging locations. Access to enterprise applications further enhances productivity by providing critical on-site information.
Climate Change and Decarbonization: The transition towards sustainable energy practices and the reduction of carbon emissions demands agile energy infrastructure. Private networks play a crucial role in supporting new methods of energy generation and storage, often in remote areas, by providing essential connectivity for real-time monitoring and control. This leads to optimized energy production and grid management, contributing to more sustainable operations.
Cybersecurity: Private networks come with enhanced security features and customization options. Energy and utility companies can implement stringent cybersecurity measures, ensuring the integrity of their critical operations and safeguarding sensitive data.
Adverse Weather and Disasters: With the increasing frequency of extreme weather events, private networks bolster observation capabilities, network resilience, and critical communication systems. During disasters, these networks enable quicker response times, efficient coordination of resources, and improved situational awareness, ultimately minimizing the impact of adverse events.
Cost-Efficiency: In the long run, private networks can prove cost-effective for energy and utility companies. They allow for precise resource allocation and streamlined processes, reducing operational costs and improving overall efficiency.

The Importance of Network Planning in the Energy Sector

In the energy sector, where uninterrupted operations are crucial, private wireless networks have emerged as essential communication lifelines. However, their true potential lies in tailored network design, a cornerstone of their efficacy.

Designing Networks for Energy Excellence

Customized network design holds immense value for the energy sector, delivering benefits that align with its distinct needs:

Optimized Resource Allocation: Customized network design in the energy sector allows for precise resource allocation, optimizing spectrum utilization and hardware placement. This strategic approach enhances cost-effectiveness and ensures efficient energy operations.

High reliability: Tailored network design considers challenging terrains and remote locations typical of energy facilities. Careful infrastructure planning, including access point and repeater placement, guarantees high reliability of the network functionality, even in remote areas.

Efficient Issue Resolution: Customized network design expedites issue identification by strategically placing monitoring and diagnostic tools throughout the network. This proactive approach minimizes downtime, preserving energy operations’ efficiency.

Enhanced Operational Performance: Tailored design optimizes network performance, ensuring consistent, high-quality connectivity. This reliability is vital for real-time energy management systems, enabling seamless monitoring and control of critical infrastructure.

iBwave: Elevating Energy Network Design

iBwave’s innovative solutions enhance energy network design by offering a range of capabilities:

Unmatched Prediction Accuracy: iBwave ensures the highest prediction accuracy, a cornerstone of reliable energy communication. You can use either iBwave Private Networks for designing Private LTE, 5G, and Wi-Fi together or our legacy best-in-class software, iBwave Design, for more complex venues and advanced features.

Versatile Network Integration: iBwave seamlessly caters to Private LTE, 5G, and Wi-Fi networks, addressing multifaceted connectivity needs in the energy industry.

Tailored Indoor/Outdoor Design for Energy Excellence: Our outdoor network planning solution, iBwave Reach, seamlessly integrates with iBwave Design to streamline campus network design, optimizing coverage for larger facilities with indoor and outdoor operational spaces that both require seamless connectivity. It leverages macro data for effective coverage planning, ensuring that all your sites are properly covered to maintain 100% uptime and operational reliability.

Seamless and Accurate On-Site Surveying: iBwave Mobile Survey, paired with the Epiq PRiSM scanner, allows you to survey and validate LTE, 5G, or Private Networks with precision and efficiency, saving you both time and costs. Unlike traditional scanners, the iBwave survey solution is lightweight, weighing under 6 ounces, and is very easy to use. There’s no need to lug around heavy, cumbersome equipment that’s difficult to operate. Just easy and cost-effective surveying.

If you want to go one step further, use iBwave Mobile Planner to start the network design on-site, using automatic access point placement to validate candidate locations as you go.

By leveraging iBwave’s solutions, energy companies elevate accuracy, streamline operations, and establish robust private networks aligned with industry-specific needs.

Conclusion

Deploying private wireless networks within the energy sector is imperative for ensuring reliable and secure communication vital to operational success. These networks offer unprecedented control, low latency, and resilience, tailored to the industry’s unique demands. Network planning and design play a pivotal role, optimizing resource allocation, ensuring uninterrupted functionality, expediting issue resolution, and enhancing overall operational performance. By combining private networks’ potential with meticulous design, the energy sector fortifies its foundation, guaranteeing efficient, secure, and uninterrupted communication vital for powering the future.

If you want to learn more about private networks for Utilities and Energy Companies, read our full eBook!

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Streamlining Network Design with GPU-Accelerated Predictions

Designing complex network infrastructures can be a time-consuming and intricate process, especially when optimizing for better efficiency and performance. Networks with multiple wireless services that span large areas such as stadiums or airports often pose significant challenges in terms of optimization and accuracy. Traditional methods relying solely on CPU calculations can struggle to handle the complexity efficiently.

The Challenge of Complex Network Design

Complex network designs require precise predictions and optimizations to ensure reliable wireless coverage and performance. However, traditional CPU-based calculations can become overwhelmed by the sheer volume of computations needed for large-scale projects.

Factors contributing to the complexity of network design include:

Diverse Environments: Networks often cover diverse physical environments with varying characteristics, such as indoor areas, outdoor spaces, open areas, and densely populated zones. Each environment presents unique challenges for signal propagation and coverage planning.
Multiple Wireless Services: Networks must support multiple wireless services concurrently, such as Wi-Fi, cellular, public safety communications, and IoT devices. Each service has specific requirements and performance criteria that must be met, adding complexity to network optimization.
Optimal Antenna Placement: Determining the optimal locations for antennas to ensure adequate coverage and minimal interference is crucial yet challenging. Antenna placement significantly impacts signal strength, coverage area, and overall network performance.
Signal Propagation Prediction: Predicting how signals will propagate within different environments, considering factors like building materials, terrain, and interference sources, is essential for achieving reliable coverage and performance.
Capacity Planning: Designing networks to handle anticipated user loads and data traffic requires careful capacity planning. Balancing capacity with coverage and signal quality is critical to avoid network congestion and ensure seamless connectivity.

Leveraging GPU Acceleration for Efficient Design

To address these challenges, the integration of GPU (Graphics Processing Unit) acceleration using NVidia’s CUDA® cores into network design workflows emerges as a transformative solution. GPUs are highly efficient at handling parallel processing tasks, making them ideal for complex mathematical computations involved in network prediction and optimization. By offloading these computations to GPUs, the overall design process can be accelerated significantly.

This acceleration is especially apparent in demanding projects like stadiums, airports, and large buildings, which traditionally require extensive time for design and network coverage prediction. With GPU-accelerated predictions, the time required to accurately predict network configurations can be reduced by significant margins—potentially saving tens of hours in complex scenarios.

Understanding GPU Acceleration Mechanics

GPU acceleration harnesses the parallel processing capabilities of graphics cards to execute computations rapidly and efficiently. Unlike traditional CPUs optimized for sequential processing, GPUs are designed with thousands of cores that can perform multiple calculations simultaneously. This massively parallel architecture enables GPUs to tackle complex mathematical operations inherent in network prediction algorithms.

The fundamental principles of GPU acceleration include:

Parallelism: GPUs excel at parallel processing, dividing tasks into smaller sub-tasks that can be executed concurrently across multiple cores. This allows for high throughput and significant speed improvements compared to CPUs.
Data-Parallel Computing: GPU algorithms are optimized for data-parallel operations, where the same operation is performed simultaneously on different data elements. This approach is well-suited for tasks like matrix multiplications and signal processing in network predictions.
Memory Bandwidth: GPUs have high memory bandwidth, enabling rapid access to data required for computations. This capability is crucial for handling large datasets efficiently during network design simulations.

Benefits of GPU Predictions

Speed: GPUs excel at parallel processing of mathematical operations, allowing for significantly faster computations compared to CPUs. This speed improvement translates to quicker predictions and optimizations, reducing design iteration times.
Scalability: GPU acceleration scales well with the complexity of network designs. As projects grow larger and more intricate, GPUs maintain performance levels, ensuring efficient processing even for demanding scenarios.
Accuracy: By processing predictions rapidly, GPU acceleration enables users to evaluate multiple design scenarios efficiently. This iterative approach leads to more accurate optimizations and improved overall network performance.
Efficiency: Leveraging GPUs for network predictions frees up CPU resources, allowing for smoother multitasking and enhanced system responsiveness during the design process.

iBwave’s Innovations in Network Design

At iBwave, we have harnessed the power of GPU acceleration to revolutionize network design capabilities. Our platform leverages GPU-based prediction algorithms to achieve remarkable performance improvements. Predictions can now be completed up to 5 times faster compared to traditional CPU methods, enabling rapid optimizations and superior network planning. With these improvements, users can save even tens of hours on very complex projects with multiple wireless services, leading to increased efficiency.

With this enhanced speed, users have more time to dedicate to fine-tuning and optimizing their network designs. The ability to iterate quickly and efficiently results in better-performing wireless networks tailored to specific environments like stadiums, airports, and large buildings.

In the table below, you can see the prediction speed improvements across several complex projects with a single wireless service compared to iBwave Release 19.2. The time savings tend to scale with the project’s complexity and the number of wireless services.

Empowering Efficient Network Design

GPU acceleration represents a pivotal advancement in streamlining complex network designs. By harnessing the computational power of GPUs, we empower users with unprecedented efficiency and accuracy in wireless network planning. This technology revolutionizes the design process, enabling faster predictions and optimizations, ultimately leading to superior network performance.

Discover how this cutting-edge technology is transforming the way networks are planned and optimized for optimal performance and reliability. Embrace the future of network design with iBwave and experience the power of GPU-accelerated predictions.

To learn more about how iBwave leverages GPU acceleration to streamline network design processes and achieve remarkable performance improvements, visit our website.

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The Most Effective Strategies for Predicting Network Coverage in Future Constructions

In the ever-evolving landscape of technology, predicting network coverage in future buildings is a crucial aspect that demands attention. The ability to anticipate how well a network will perform within a structure is paramount for providing optimal connectivity and ensuring a seamless user experience. In this blog post, we’ll delve into the why, the key benefits for customers, and the most effective strategies for predicting network coverage.

Why Predict Network Coverage for Future Buildings?

Understanding the motivations behind predicting network coverage is fundamental to appreciating its significance. As technology advances, our reliance on robust connectivity grows exponentially. Whether it’s for everyday communication, smart home applications, or business operations, a strong and reliable network is the backbone of modern living.

Differences Between Existing and Future Buildings

Future building designs, especially those focused on energy efficiency, present distinct challenges for network coverage compared to traditional structures. As highlighted in our recent webinar, upcoming constructions are mandated to comply with rigorous thermal insulation regulations, resulting in what are known as energy-efficient buildings.

These energy-efficient buildings, often equipped with materials like low E glass and specialized insulation, pose significant challenges for robust network coverage. Unlike traditional constructions that typically exhibit lower transmission losses, future buildings demand a reevaluation of network prediction strategies.

The use of low E glass, designed to minimize heat transfer, inadvertently amplifies signal attenuation for radio waves, resulting in approximately 30 decibels of signal loss—equivalent to the obstruction caused by a concrete wall. This discrepancy between traditional and future buildings necessitates tailored approaches for anticipating and mitigating coverage issues.

Source: Waveform

Main Challenges in Predicting Network Coverage

Predicting network coverage in modern buildings presents several significant challenges, including:

Material Impact on Signal Propagation: The choice of modern construction materials, such as low E glass and specialized insulation, significantly impacts signal propagation, resulting in increased attenuation and coverage challenges.

Source: Wilson Amplifiers

In the image below, you can see how little outdoor signal can penetrate the walls inside of a modern low E glass building, resulting in many areas without a network connection.

Resource-Intensive Surveys: Conducting thorough site surveys to assess network conditions within modern buildings is resource-intensive, demanding substantial time and effort. Access constraints and logistical hurdles further complicate this process, potentially leading to delays in network deployment.

Optimization vs. Over-Engineering: Balancing network design optimization with cost-efficiency is crucial. Over-engineering can inflate project costs by necessitating an excess of antennas, while under-engineering may result in inadequate coverage, necessitating costly post-installation optimizations.

Integration of External Data Sources: Integrating external data sources, such as macro network details, poses challenges in ensuring accuracy and reliability. While ideal scenarios involve direct data acquisition from network operators, alternative sources like crowdsourced coverage maps and governmental databases often serve as viable substitutes.

Key Benefits of Predicting Network Coverage

Seamless Connectivity: Predicting network coverage ensures that customers experience uninterrupted connectivity, enabling them to stay connected with their digital world effortlessly.
Enhanced User Experience: Anticipating and addressing potential network issues in advance leads to an improved user experience. Customers can enjoy faster data speeds and smoother performance on their devices.
Future-Proofing Investments: For property owners and developers, predicting network coverage is a strategic move. It allows them to future-proof their investments by incorporating the latest connectivity solutions, making their properties more attractive to potential occupants.

Effective Strategies for Predicting Network Coverage

1. Survey Data Analysis: The Foundation of Prediction

One of the primary strategies is leveraging survey data. Conducting thorough surveys of the building’s interior helps in understanding the existing network landscape. The key use case involves identifying potential dead zones or areas with weak signals. The advantages of this approach include precise insights into the current network scenario within the building.

Advantages:

Precision: Survey data analysis provides detailed and precise information about the existing network conditions.
Targeted Improvements: Identifying specific areas with weak signals allows for targeted improvements to enhance coverage.

Challenges:

Resource-Intensive: Conducting thorough surveys can be resource-intensive, requiring time and effort.

2. Inbuilding Prediction with Antenna Positioning

Another approach focuses on in-building prediction using different antenna positions. This strategy involves strategically placing antennas around the building to simulate and predict network coverage. The key use case is to optimize antenna placement for maximum coverage.

Advantages:

Optimized Placement: Antennas can be strategically placed for optimized coverage, reducing potential dead zones.
Cost-Effective: Simulating antenna positions in a virtual environment can be more cost-effective than physical adjustments.

Challenges:

Simulation Variability: Real-world conditions may introduce variability not accounted for in simulations.

3. Geo/Macro Data Integration for Comprehensive Insights

The third strategy involves geo/macro data integration to predict coverage accurately. This comprehensive solution considers external factors and introduces the concept of using iBwave Reach for precise predictions.

Advantages:

Holistic Analysis: Geo/macro data integration provides a holistic analysis of external factors impacting network coverage.
Precision: With iBwave Reach, cou can enhance prediction precision with advanced capabilities.

Challenges:

Data Integration Challenges: Integrating external data sources may pose challenges in ensuring accuracy. However, with iBwave Reach, these challenges disappear thanks to its seamless integration with our inbulilding design tool iBwave Design.

How iBwave Can Help

Leveraging iBwave’s suite of solutions, including iBwave Reach, Design, and Mobile Survey, significantly aids in predicting network coverage effectively. For example, iBwave Reach facilitates real and accurate data integration, considering elevation, surroundings, and more. The seamless integration between iBwave tools eliminates challenges in data integration, ensuring a comprehensive and precise approach to predicting network coverage.

Here’s how our tools can help you predict network coverage:

Survey Data Analysis – iBwave Mobile & iBwave Design

iBwave Mobile is a simple and cost-effective solution empowering field technicians to survey LTE, 5G, Wi-Fi, or P25 Public Safety Networks quickly and seamlessly. iBwave Mobile – our simple mobile application seamlessly integrates with a lightweight and powerful Epiq PRiSM scanner for deeper scanning of wireless networks.

iBwave Mobile also integrates with our flagship solution for designing in-building networks, iBwave Design. Thanks to this integration, you can easily interpolate the survey data and predict the network coverage inside of your future building.

In-Building Prediction with Antenna Positioning – iBwave Design

iBwave Design is the industry standard solution for designing the best-in-class inbuilding wireless networks. You can easily position antennas around the building and simulate their performance and penetration in the building at different heights and floors.

Geo/Macro Data Integration – iBwave Reach

iBwave Reach is a solution for designing campus networks that bridges the gap between indoor and outdoor wireless. By integrating the macro network data, you can see its effect on the indoor wireless networks and penetration inside of the building. iBwave Reach considers elevation and surrounding buildings, giving you the most accurate predictions. Another advantage is its integration with iBwave Design, bridging the data integration challenges.

Conclusion: Empowering Connectivity in the Future

In conclusion, predicting network coverage is not just about ensuring connectivity; it’s about empowering the future. By understanding the motivations, benefits, and effective strategies, stakeholders can make informed decisions. iBwave’s solutions play a pivotal role in navigating the complexities of network prediction, making it an indispensable ally in the journey towards seamless connectivity.

Don’t miss out on the deeper insights! Watch our on-demand webinar with our special guest, STF Gruppe, to learn everything about predicting network coverage in future constructions.

Check out our blog for more tips and topics to learn more about wireless networks and their planning!