Here at HASC, modelling and measurement is a core element of our research – it is one of the four connectivity challenges we are exploring. In this post we explain modelling and measurement in more detail and discuss our approach to the challenge of combining wired and wireless internet technologies. Let’s get into it!

The Complexity of Modern Connectivity

The demands for connectivity are increasing exponentially. In today’s modern world, work has become borderless, mobile-first economies are booming and global audiences are becoming more diverse and more demanding than ever before. Our world is rapidly changing, as is our demand for faster, more agile connectivity. All this leads to greater complexity. As global connectivity expands and diversifies, communication networks need to keep up.

The Challenge of Managing Wired & Wireless Infrastructure

Traditionally, wired and wireless networks have been managed separately, with each being optimised individually for specific use cases. But with growing demand and ever more sophisticated requirements we must make better use of the spectrum as a whole.

To achieve the type of connectivity we need now, and, in the future, we must manage both resources as one unified entity. This means combining optical and radio frequency (RF) infrastructure… and this is where modelling can help.

What Is Modelling and Why Does It Matter?

To understand how we can improve connectivity, we first need the tools that help us test ideas safely and effectively. Modelling gives us exactly that. Modelling allows us to create digital representations of complex real-world networks and systems. These models help researchers and engineers simulate different scenarios, test new ideas, and predict how networks will behave under changing conditions. And all this without the cost or disruption of real-world trials. In the context of wired and wireless systems, modelling is crucial to understanding the interplay between technologies and identifying smarter, and sometimes more sustainable ways to deliver high-performance connectivity.

Analytical and Simulation-based Modelling Explained

Did you know there are different types of modelling? Here, we explain the differences between ‘analytical’ and ‘simulation-based’ modelling.

Analytical modelling

Analytical modelling uses maths and logic to describe how a system should behave, often resulting in equations that reveal core principles, such as how signals propagate (how they travel from transmitter to receiver in different environmental conditions).

Simulation-based modelling

Simulation-based modelling, by contrast, involves running virtual experiments using software. It allows us to test real-world conditions, explore ‘what if’ scenarios by adding new variables, and validate the ideas developed during the analytical stage.

HASC’s Approach to All Spectrum Connectivity & Modelling

At HASC, we’re not studying networks in ‘silos’, we’re building models that treat wired (optical/fibre) and wireless (radio frequency) infrastructure as one interconnected system. This approach allows us to explore how these technologies can best work together. We use a framework that includes both analytical and simulation-based modelling to illustrate and better understand how to optimise different combinations of the spectrum. We are experimenting with how both wired and wireless channels can be used together across various applications and in many different environments.

A Holistic Network Model

This unified approach will allow us to:

• Capture the interactions between different network layers, network types, and technologies.
• Observe multiple variables across both systems, such as bandwidth, latency, energy use, traffic load, and environmental factors.
• Re-create real-world complexity, rather than assuming ideal or simplified conditions for just one part of the network.

In new and emerging environments like smart cities, connected transport, or connected healthcare both types of connectivity need to be used together – often dynamically.

A Look Inside A HASC Modelling Project

One of the most ambitious modelling projects underway at HASC focuses on understanding how signals travel at ultra-high frequencies like mmWave, THz, and even light-based wireless. Here’s how that work is unfolding.

Enhanced channel measurement and modelling

mmWave, THz, Optical channel measurements and modelling

Project Led by Simon Cotton, QUB

This project supports the development of next-generation wireless technologies, such as 6G, by advancing our understanding of how high-frequency signals behave in real-world environments.

Measuring & Modelling Wireless

In the early stages, we’re focusing on measuring and modelling how wireless signals propagate through the air at mmWave and THz frequencies. These bands are essential for enabling ultra-high-speed, low-latency connectivity in future networks. The data we generate is being shared with key international standards bodies such as IEEE 802.11, 3GPP, and ETSI. By sharing this data, we are ensuring that the insights we uncover can help shape the technical foundations of tomorrow’s wireless systems.

Smart Environments

In parallel, we’re developing models for novel environments that use reconfigurable surfaces, known as RIS (Reconfigurable Intelligent Surfaces) and RIE (Reconfigurable Intelligent Environments), to actively control how signals move through space. These smart environments can dynamically optimise signal paths, reduce interference, and enhance energy efficiency. Our modelling work is informing standards evolution within the ETSI (European Telecommunications Standards Institute) RIS ISG (Industry Specification Group on Reconfigurable Intelligent Surfaces) and contributing to a more agile and sustainable future network design.

Beyond Standards: The Broader Impact

The data and models produced through this project will do more than just feed into standards. They will help lay the groundwork for intelligent spectrum-sharing strategies, inform regulatory guidance and support future applications like autonomous mobility, immersive communications, and energy-aware network design. The ability to model, predict and optimise channel behaviour across such a wide range of frequencies will be vital as we move toward a more connected, more complex, and context-aware digital infrastructure.

Conclusion

Feeding into IEEE, 3GPP and ETSI is essential but beyond that, modelling projects like this help to accelerate innovation, ensure greater interoperability, and are helping to lower development barriers. Furthermore, open data contribute towards a more collaborative approach to technological advancements. It enables researchers across the globe, from academia and industry as well as supporting regulators. Ultimately, modelling is not just a technical task. It’s a strategic enabler for future digital ecosystems. Whether it’s autonomous transport, real-time healthcare, or immersive virtual experiences, the networks of tomorrow will rely on the modelling insights we’re building today.

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