MIMO Systems in SmallSat Swarms: System Characterization With the Introduction of a Channel Model

Abstract

This work introduces a multiple-input multiple-output (MIMO) channel model to characterize propagation in a small satellite swarm environment. By using the Rician <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$K$ </tex-math></inline-formula> -factor, this model appropriately combines fixed line-of-sight (LoS), satellite-reflected, and earth-reflected (ER) channel components with a randomly varying diffuse component that accounts for satellite, earth, and atmospheric scattering. The proposed model is compared to ray tracing and used to elucidate the performance of (4, 4), (8, 8), and (16, 16) point-to-point MIMO systems. Indicatively, assuming 15 dBm of transmit power, a keep-out radius of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$R_{KO} \geq 50$ </tex-math></inline-formula> m, and a 24 satellite swarm, (16, 16) MIMO systems achieve approximately 4–5 times the capacity of a (2, 2) polarization diversity-based system, a significant improvement for a swarm that operates as a fractionated system and autonomously makes decisions. It is also shown that a (16, 1) single-input multiple-output system has 130 times the range of a (2, 1) system, increasing proportionally the lifetime of the swarm as satellites drift apart. With an example power budget, we show that a 3U CubeSat with an orbit average power (OAP) of 12.9 W can support 16 MIMO antennas. This MIMO channel model is the first step in developing optimized communication systems for SmallSat swarms.