Beamspace MIMO for Satellite Swarms

TL;DR

This paper proposes a distributed beamforming scheme for satellite swarms communicating with ground stations, leveraging local position info to achieve near-optimal spectral efficiency without requiring inter-satellite cooperation.

Contribution

It introduces a novel position-based precoding method for satellite swarms that operates effectively despite rapid channel variations and no inter-satellite communication.

Findings

Achieves 99.8% of maximum rate with local position info

Optimal inter-satellite distance derived analytically

Effective without inter-satellite cooperation or perfect CSI

Abstract

Systems of small distributed satellites in low Earth orbit (LEO) transmitting cooperatively to a multiple antenna ground station (GS) are investigated. These satellite swarms have the benefit of much higher spatial separation in the transmit antennas than traditional big satellites with antenna arrays, promising a massive increase in spectral efficiency. However, this would require instantaneous perfect channel state information (CSI) and strong cooperation between satellites. In practice, orbital velocities around 7.5 km/s lead to very short channel coherence times on the order of fractions of the inter-satellite propagation delay, invalidating these assumptions. In this paper, we propose a distributed linear precoding scheme and a GS equalizer relying on local position information. In particular, each satellite only requires information about its own position and that of the GS, while the GS has complete positional information. Due to the deterministic nature of satellite movement this information is easily obtained and no inter-satellite information exchange is required during transmission. Based on the underlying geometrical channel approximation, the optimal inter-satellite distance is obtained analytically. Numerical evaluations show that the proposed scheme is, on average, within 99.8% of the maximum achievable rate for instantaneous CSI and perfect cooperation