Rate-Splitting Multiple Access for GEO-LEO Coexisting Satellite Systems: A Traffic-Aware Throughput Maximization Precoder Design

TL;DR

This work tackles spectrum sharing between GEO and LEO satellite systems under in-line interference, introducing a rate-splitting multiple access (RSMA) scheme with a super-common message to aid GEO users in decoding interference. The authors formulate a traffic-aware throughput maximization (TTM) problem that allocates RSMA power across a super-common, common, and private streams to satisfy heterogeneous traffic demands within a total power budget, using semidefinite relaxation (SDR) and concave-convex procedure (CCCP) to convexify the problem and a feasibility-restoration step to ensure IL and power constraints are met. The proposed SPC-RSMA TTM demonstrates near-full traffic satisfaction (e.g., average around 98% in simulations) and robust LEO throughput even in the in-line interference regime with imperfect CSIT/CSIR, outperforming conventional SDMA, MMF, and other interference-management schemes. The results indicate practical applicability for GEO-LEO coexisting systems, including multi-LEO scenarios where throughput remains resilient to additional interference. Overall, the method offers a flexible, low-signaling-demand approach to interference management and traffic-driven precoding in next-generation satellite networks, with potential for real-world deployment under regulatory constraints such as ITU Article requirements. $R_{ m spc}$, $R_{ m c}$, $R_{ m p}$, and $T_j$ are optimized under constraints including $I_{ m th}$ and power $P_{ m L}$ with the objective of maximizing satisfied throughput $ extstyle \sum_{j=1}^{K_{ m L}} extstyle \min ig(T_j, R_jig)$. $R_j$ denotes the achievable rate for LU $j$, and the framework accommodates imperfect CSI via GMI-based rate expressions. $X$-matrix SDRs, CCCP linearization, and a randomization step ensure feasible precoding vectors even when rank-one solutions are not obtained on the relaxed problem.

Abstract

The frequency coexistence between geostationary orbit (GEO) and low earth orbit (LEO) satellite systems is expected to be a promising approach for relieving spectrum scarcity. However, it is essential to manage mutual interference between GEO and LEO satellite systems for frequency coexistence. Specifically, \emph{in-line interference}, caused by LEO satellites moving near the line-of-sight path between GEO satellite and GEO users (GUs), can significantly degrade GEO system throughput. This paper put forth a novel rate-splitting multiple access (RSMA) with a super-common message for GEO-LEO coexisting satellite systems (CSS). By employing a super-common message that GUs can decode, GUs can mitigate the in-line interference by successive interference cancellation (SIC). Moreover, we formulate a traffic-aware throughput maximization (TTM) problem to satisfy the heterogeneous traffic demands of users by minimizing total unmet throughput demands (or user dissatisfaction). By doing so, the TTM precoder can be flexibly adjusted according to the interference leakage from LEO satellites to GUs and target traffic demands. Numerical results confirm that our proposed method ensures seamless connectivity even in the GEO-LEO in-line interference regime under imperfect channel state information (CSI) at both the transmitter and receiver.

Figures (4)

• Figure 1: GEO-LEO CSS system model based on RSMA.
• Figure 2: LU throughput according to LU positions under imperfect CSIT and CSIR ($\sigma_{e}^2 = 0.05$).
• Figure 3: LEO system throughput as a function of GU off-boresight angle under imperfect CSIT and CSIR ($\sigma_{e}^2 = 0.05$).
• Figure 4: LEO system throughput as a function of separation angle between the LEO satellites under imperfect CSIT and CSIR ($\sigma_{e}^2 = 0.05$).