Static beam placement and frequency plan algorithms for LEO constellations

Abstract

LEO satellites are growing rapidly in number, but also in configurability of the payload, which presents new challenges of how to allocate the satellite's resources. We present an algorithm to solve two subproblems of the resource allocation problem for multi-beam satellites in large LEO constellations. Our approach produces a static beam placement and a static frequency plan, taking into account the user demands and interference conditions, respectively. We provide an easy to implement and fast approximation for the beam placement problem, which is converted into an Edge Clique Cover problem using graph theory. The frequency assignment problem is translated into a constraint satisfaction problem, which is later solved with a first-fit heuristic. We apply our algorithm to a scenario based on SpaceX's Starlink constellation, and when compared to two different baselines, we show that our method requires 40% fewer beams while being able to provide service to 2% more users.

Efficient Hamiltonian Reduction for Quantum Annealing on SatCom Beam Placement Problem

“…To exploit users' traffic diversity and maximize multicast benefits, the satellite aims at minimizing the number of active beams while ensuring the requested service by its users [3], [4]. To do that, nearby users can be served by the same beam.…”

“…To do that, nearby users can be served by the same beam. Leveraging the results of previous works [3], [19], to be served in the same beam, with the specific location of the satellite, any pairs of a given set of users must be separated by an angle ᾱ ≤ α 2 , where α is the cone angle of a beam. This is illustrated in Fig.…”

“…Operators may prefer to reduce the number of beams generated on-board so that the beamforming network is kept as simple as possible. The works in [3], [4] represent the latest approaches to the beam placement problem. Both works faced the trade-off between minimizing the number of beams and maximizing the provided gain to users.…”

“…Both works faced the trade-off between minimizing the number of beams and maximizing the provided gain to users. However, what is relevant here is that both [3] and [4] formulate the beam placement problem as a minimum clique cover problem, which is an NP-hard problem and therefore intractable for a classical computer to solve. Given the emergence of commercial quantum computers, we investigate the possibility of using quantum computing for this problem.…”

Emerging IoT domains, current standings and open research challenges: a review

“…Starlink project is expected to launch over 30,000 TinTin satellites in the next decade to provide umbrella high-speed internet coverage to remote parts of the world. These satellites form constellations by using laser beams to communicate with each other (Liu et al, 2020;De la Osa et al, 2021). Other aspects that enable satellite networks as future communication link contenders are their ability to provide flexible bandwidth and very high data rates ranging up to Gigabits per second (Sansone et al, 2020).…”