Communication System Modelling

Virtual freedom to put novel ideas to the test rapidly and at a lower cost

Mimicking what’s going on in the real world is at the heart of communication system modelling – giving the freedom to explore and experiment with changes from the safety of a computer to see what works best.

It involves understanding and simulating all aspects of a communication system, including the environment it needs to operate in, how the radio waves propagate in that environment and how any device will be moving through it – in a car or aircraft, for example.

The environmental considerations could be something as simple as weather – heavy rain is a problem for certain frequencies, for example – or it could involve simulating solar rays in the upper atmosphere for satellite communications.

Smart city or industrial automation applications can be evaluated without having to build an actual test network – and communication systems for special events can be stress tested in advance to determine the WiFi capacity required for the expected attendance figures.

Real-world challenges

Reducing costs of a radio system

When a client wanted to reduce the costs of the radio system controlling its autonomous industrial equipment, the Plextek team was asked to investigate possible alternatives and evaluate whether they would give the necessary performance.

The most promising option was a new generation of WiFi that looked like it had some off-the-shelf features that would fit the bill. However, modelling the multi-user system revealed an issue with the scheduler, which was optimised for families streaming high-bandwidth video at home – it struggled to cope with the client’s low-bandwidth application involving a lot more users.

By identifying the key aspect that needed improving for the system to meet the client’s performance requirements, the modelling enabled the client to explore the potential of writing their own scheduler for the low-cost WiFi option.

Metamaterials for the propagation of RF

Metamaterial surfaces and structures offer interesting opportunities for novel antenna designs – they are artificial materials that exhibit unusual electromagnetic properties not found in naturally occurring materials.

To investigate the use of metamaterials for the propagation of radio frequency (RF) energy via surface waves, the Plextek team designed, simulated and fabricated a number of metamaterial surfaces as part of a research project.

Measurements showed excellent agreement with simulations and proved the effectiveness of metamaterial surfaces for surface-wave transmission of RF energy.

Key skills

  • Advanced modelling and simulation

    Proficiency in using simulation tools (e.g. MATLAB, ns-3, Python) to model complex communication systems and assess their performance under various scenarios.

  • Efficient RF and signal processing techniques

    Extensive experience in RF engineering and applying advanced signal processing techniques to mitigate interference and improve system capacity.

  • Wireless system design and optimisation

    Capability to design and optimise wireless communication systems, including WiFi and 5G networks, using knowledge of protocols and channel characteristics.

  • Internet of Things (IoT) and smart systems development

    Proficiency in designing low-bandwidth applications for IoT devices, including network planning and protocol design tailored for smart city and industrial automation.

  • Link budget and network planning

    Competence in performing link budget analysis and strategic network planning for both cellular and ad hoc networks to ensure coverage and capacity.

  • Practical implementation of theory

    Experience in translating theoretical models and simulations into real-world applications, demonstrating technological agility and innovation.

Modelling allows us to try out a wide variety of configurations, test how the system performs under difficult circumstances or evaluate novel techniques. This can be done much more rapidly and at a lower cost than building an actual test network. It also allows us to try things which may be difficult to achieve or rare in the real world, find out how it scales or evaluate technologies which are not yet available.

Dr Tom Rouse, Principal Consultant
Dr Tom Rouse

Principal Consultant

What sets us apart in communication system modelling?

Plextek’s wide range of skills and experience enables us to choose the right tools and produce accurate results which are relevant for each specific application, including:

  • 5G
  • AI & ML in communication systems
  • Cellular and ad hoc network planning
  • Channel interference
  • High-bandwidth streaming optimisation
  • Link budget
  • Low-bandwidth IoT applications
  • MATLAB
  • Mobility and fading models
  • Multi-user system modelling
  • ns-3 simulator for network analysis
  • Protocol design and optimisation
  • Python
  • RF propagation
  • Signal processing
  • Simulation tools for network planning
  • WiFi capacity planning
  • Wireless communications
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an image of our technical paper
Analysis of Chilton Ionosonde Critical Frequency Measurements During Solar Cycle 23 in the Context of Midlatitude HF NVIS Frequency Predictions

This paper presents a comparison of Chilton ionosonde critical frequency measurements against vertical-incidence HF propagation predictions using ASAPS (Advanced Stand Alone Prediction System) and VOACAP (Voice of America Coverage Analysis Program). This analysis covers the time period from 1996 to 2010 (thereby covering solar cycle 23) and was carried out in the context of UK-centric near-vertical incidence skywave (NVIS) frequency predictions. Measured and predicted monthly median frequencies are compared, as are the upper and lower decile frequencies (10% and 90% respectively). The ASAPS basic MUF predictions generally agree with fxI (in lieu of fxF2) measurements, whereas those for VOACAP appear to be conservative for the Chilton ionosonde, particularly around solar maximum. Below ~4 MHz during winter nights around solar minimum, both ASAPS and VOACAP MUF predictions tend towards foF2, which is contrary to their underlying theory and requires further investigation. While VOACAP has greater errors at solar maximum, those for ASAPS increase at low or negative T-index values. Finally, VOACAP errors might be large when T-SSN exceeds ~15.

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