Load Balancing in Non-Terrestrial Networks Using Free Space Optical Inter-satellite Links

Abstract

Non-terrestrial networks (NTNs) increasingly rely on non-geostationary (NGSO) constellations that combine radio frequency (RF) feeder links (FLs) with free space optical (FSO) inter-satellite links (ISLs). Downlink performance in such systems is often constrained by uneven satellite-gateway visibility, data traffic congestion, and rain-induced FL attenuation, leaving the downlink capacity of some satellites underutilized while others become bottlenecks. To prevent such non-uniform load distribution, this paper presents a fairness-driven load balancing strategy that treats the satellite constellation in space as an anycast multi-commodity flow problem. Then, by solving an equivalent linear programming optimization problem, the proposed algorithm dynamically selects the most convenient ground station (GS) to serve each satellite and, when needed, offloads data traffic to adjacent satellites through FSO ISLs. Using a realistic MEO satellite constellation with 1550 nm FSO ISLs and Ka-band feeder links, the method stabilizes the reverse link data service, maintaining the average data rate but notably improving the worst-case throughput. Our proposed algorithm enhances the minimum downlink data rate by more than 25% in the presence of rain and by over 10% under no-rain conditions. These results demonstrate that the use of an ISL-assisted load-balancing scheme mitigates FL bottlenecks and enhances fairness across the satellite constellation, offering a scalable basis for resource allocation in future NTN systems.

Figures (5)

• Figure 1: (a) Overview of a multi-satellite constellation with $K$ satellites serving $I$ ground stations. Each satellite forms a single Ka-band feeder link to its serving GS. The achievable FL capacity varies with geometry, off-axis angles ($\phi$ and $\theta$), and rain attenuation. The red FL indicates a weather-degraded connection affected by rain, whereas the green FLs represent no-rain conditions. The adjacent satellites are connected by optical ISL with fixed capacity. These ISLs offload traffic from satellites with weak feeder links to neighbors with stronger feeder links, improving constellation download rate and fairness. (b) Equivalent representation of the multi-satellite system in the form of a time-varying graph. Satellite $k$ downloads data to GS $i$ directly or via neighboring satellites (with satellite indexes $k\pm1$) using ISLs.
• Figure 2: Rain attenuation (dB) across different elevation angles.
• Figure 3: SES O3b mPOWER system architecture showing the equatorial orbit (blue line). Red stars indicate ground stations, and blue dots mark satellite positions at a given time instant.
• Figure 4: Throughput distribution histograms for satellites F-01 to F-06 under clear sky conditions. For each satellite, red histograms represent the throughput distribution without inter-satellite links (ISL), while blue histograms correspond to the case with ISL enabled. For each satellite, the solid blue vertical line indicates the mean throughput, whereas the dashed vertical lines denote standard deviation above and below the mean for the respective no-ISL and ISL cases.
• Figure 5: Downloaded data rate comparison for the six satellites in a $24$-hour window. The light red, light blue, and light green patches indicate heavy rain at Santiago GS, moderate rain at Dubbo/Pivotel GS, and light rain at Phoenix/AZ GS, respectively. The black curves show the no-ISL throughput, with red markers showing the worst-case values under different rain conditions, whereas the blue curves indicate the throughput achieved with ISL.