Published on 31.05.2021 | Last updated on 26.09.2024
The continuously growing satellite communications traffic is becoming a burden on the satellites. To solve this problem, Magister built a simulator that optimizes the use of resources. It makes sure that resources are where they are most needed – when they are needed.
As the need for satellite communications grows, LEO satellites get increasingly more burdened. Related to this, however, a question arises. Why should LEO satellites share their capacity evenly, even though demand varies by location, population density and time of day?
Through intelligent resource management, there’s a possibility to optimize the use of the capacity – based on life on Earth.
Together with Thales Alenia Space France, we at Magister developed a resource management algorithm in ESA’s C-DReAM project. The algorithm is able to optimize the allocation of resources of a non-geostationary satellite orbit (NGSO) satellite constellation.
By adjusting to the capacity on-a-need-basis, the NGSO constellation can provide more capacity to peak times and areas and improve the quality of services. The network capacity can also be dimensioned based on the average volume likely reducing the cost of the system.
The C-DReAM project started in 2021 and was completed in 2022.
NGSO satellite constellation – Matching capacity to demand
The use of a current NGSO satellite constellation offers many advantages for communication missions. These include, for example, potential global coverage, low delay transmission, increased robustness, and potentially lower costs of gigabit per second.
However, there are also challenges. The SatCom capacity is traditionally distributed uniformly, but the data demand is not. Therefore, the actual system throughput can be severely limited.
So, what needs to change? Satellite networks should introduce flexible payloads that allow them to match the capacity to the actual traffic demand. This way, they could maximize their throughput.
“We need to get more capacity to peak times and areas. Could it be done by moving the capacity, bandwidth and/or time to more crowded areas and busier times of the day? Or through aggressive frequency reuse and by downsizing the beams over smaller areas? There are several possibilities, so we need an algorithm that can find a “good enough” allocation in a reasonable amount of time”, explained Janne Kurjenniemi, the former Research Director of Magister Solutions.
The simplest solution – heuristic strategies – would allow NGSO satellite constellations to converge to a suboptimal solution in a single iteration. However, more advanced and more complex iterative optimization algorithms would allow reaching better performance – but also with longer convergence times.
The best solution probably lies somewhere in between: an acceptable trade-off between system performance and convergence time. During C-DReAM, we implemented and evaluated the algorithm options through Magister’s software simulator.
Simulating the resource management algorithm
In the project, Magister and Thales Alenia Space France worked together to find the most suitable algorithms. Thales Alenia Space France set the requirements, defined the scenario and examined how the resources should be shared. Magister was responsible for simulator design, development, simulations executions and analysis of the results.
The resource management algorithm can optimize the resource allocation of a NGSO satellite constellation. The optimization is based on the geographical and temporal variations in the traffic demand. It also demonstrates how such an algorithm can converge fast enough to be operationally useful.
“We will develop a software simulator that models the NGSO system in terms of traffic, user terminal characteristics, channel model, antenna and payload model, orbit propagation, and so on. The resource allocation algorithms shall be evaluated with our simulator, for example, in terms of throughput performance and run-time complexity”, Kurjenniemi stated.
Through the system demonstrator, users can configure different system scenarios, such as satellite constellations. The system demonstrator can also interface with alternative radio resource management (RRM) algorithms, potentially developed by the user.
