Guest Blog: Developing algorithms to optimise satellite communications
Guest blog from Lorna Ashton, Business Development Manager - Spectrum & Security at The Smith Institute
Satellite communications systems underpin all aspects of our increasingly mobile and data-rich lives. They support business and leisure activities over the world, providing reliable and high-speed connectivity as customer expectations rise with the acceleration of the digital transformation of our lives, businesses, and governments.
To cope with the increase in the modern world’s demand for data without impacting the connection, speed, or quality, satellite operators can consider launching new satellites to support the existing fleet.
A second, more cost-effective possibility is optimising the output of existing satellites to ensure they are operating at maximum efficiency. This can be more economical, sustainable and reduce the risk of increasing space debris and other operational complications.
We recently supported a leading satellite communications business with this exact challenge. They needed to manage the massive rise in satellite data requirements without compromising on the quality of customer experience. Inmarsat, who connect people across the globe on land, sea and air, needed to consider all options.
Launching new satellites to cope with increased demand is expensive, both financially and environmentally. Satellite operators are under increasing pressure to reduce the risk of space debris, on-orbit collisions, and unsustainable space operations. A more economical option is to increase capacity by optimising the operations of existing assets to service customers more efficiently.
To achieve this optimal radio resource capacity management, the operator required the ability to model and solve a complex set of scenarios with offline optimisation. The team realised that this would require expertise in constructing the right models and algorithms, together with an understanding of how to transform these into actionable solutions.
We worked closely with Inmarsat’s radio resources management team to understand the current operating methods and the challenges they faced. Once we had gained a good grounding in the specifics of their operation, we set about creating a model of the existing system against which we would be able to benchmark new methodologies. This would ensure we could prove the value of any proposed solution.
Effective radio resource management for satellite communications must consider how the specifics of each device communicating with the satellite network is affected by a complex interplay of symbol rates, modulation options, error checking and correction, energy consumption and atmospheric conditions.
Each of Inmarsat’s satellites needed to be able to offer a set of characteristics that created as smooth an experience as possible for all the devices requesting its services. The algorithm had to consider the prevailing conditions whilst having the flexibility to adjust certain characteristics if conditions or capabilities change. In addition, the operation of Inmarsat’s service needs to comply with legal, regulatory and contractual obligations.
To manage this complexity, we took a two-stage approach. Firstly, we constructed a genetic algorithm programmed to assemble and analyse a set of likely transmission scenarios from which it could determine a combination of traffic carriers favourable to meet anticipated demand in the prevailing conditions. The optimal traffic carrier combinations could then be fed into our second stage algorithm which creates the bandwidth bundles best suited to meeting current, recognised demand.
The solution is expected to allow the business to identify satellite beams with underperforming bandwidth bundles and optimise and reconfigure these to increase the utilisation efficiency. Initial results suggest that this will allow an increase in efficiency of 20 to 40% in the most congested geographical areas. Considering the scarcity of satellite resources, this represents a significant improvement in resource utilisation and end-customer satisfaction.
Other Possible Use Cases of Optimisation in the Satellite Industry
With a growing number of satellites in space, the risk of on-orbit collisions with space debris and other satellites is increasing. Satellites are highly valuable assets, both in their cost of deployment and in the services they support, making them very difficult to repair and maintain. In addition, evasive interventions to mitigate the collision risk are costly as satellites only have a finite amount of fuel on board for manoeuvring. Consequently, this limited resource must be used sparingly.
Given the rising risk of collisions with space debris and the drive towards sustainable space traffic management, optimising for the longest operational satellite lifetimes has become an increasingly difficult challenge and having a reliable solution is more of a priority than ever before. Thankfully, Mathematical Optimisation and Decision Intelligence has the potential to enable these solutions.
This optimisation could range from:
- Modelling the available satellite bandwidth to increase operational efficiency
- Forecasting and managing the degradation of satellites
- Ensuring sufficient fuel is available throughout the lifespan of satellites by optimising fuel usage – potentially extending satellite life expectancy.
This would enable operators to analytically quantify risks to these valuable assets and increase the efficiency of decision making for position correction, intervention and inspection.