Coverage and Spectral Efficiency of NOMA-Enabled LEO Satellite Networks with Ordering Schemes

TL;DR

This work develops a stochastic-geometry-based framework to analyze downlink NOMA in dense LEO satellite networks with inter-satellite interference and SIC imperfections, using MSP- and ISINR-based user ordering. It derives coverage-probability expressions and evaluates fairness-aware PA schemes (ETPA, ERPA, FPA) alongside OMA benchmarks, validating results via simulations and exploring the impact of LoS, RI, main-lobe gains, and satellite density. Key findings show LoS benefits and SIC efficiency improve coverage, a tradeoff between the number of satellites and altitude to maximize mean coverage, and that NOMA can offer up to 35% SE gain over OMA when the SINR is favorable, with the maximum SE occurring for two UTs. The results provide practical design guidance for NOMA-enabled LEO constellations, informing ordering and PA selections to balance spectral efficiency and decoding complexity in real deployments.

Abstract

This paper investigates an analytical model for low-earth orbit (LEO) multi-satellite downlink non-orthogonal multiple access (NOMA) networks. The satellites transmit data to multiple NOMA user terminals (UTs), each employing successive interference cancellation (SIC) for decoding. Two ordering schemes are adopted for NOMA-enabled LEO satellite networks, i.e., mean signal power (MSP)-based ordering and instantaneous signal-to-inter-satellite-interference-plus-noise ratio (ISINR)-based ordering. For each ordering scheme, we derive the analytical expression for the coverage probability of each typical UT. Moreover, we discuss how coverage is influenced by SIC, main-lobe gain, and tradeoffs between the number of satellites and their altitudes. Additionally, two user fairness-based power allocation (PA) schemes are considered, and PA coefficients with the optimal number of UTs that maximize their sum spectral efficiency (SE) are studied. Simulation results show that there exists a maximum effective signal-to-inter-satellite-interference-plus-noise ratio (SINR) threshold for each PA scheme that ensures the operation of NOMA in LEO satellite networks, and NOMA provides performance gains only when the target SINR is below a certain threshold. Compared with orthogonal multiple access (OMA), NOMA increases UTs' sum SE by as much as 35%. Furthermore, for most SINR thresholds, the sum SE increases with the number of UTs to the highest value, whilst the maximum sum SE is obtained when there are two UTs.

Figures (14)

• Figure 1: An illustration of NOMA-enabled LEO multi-satellite networks.
• Figure 2: Distance from typical satellite to typical UTs.
• Figure 3: Distance from typical UTs to satellites.
• Figure 4: Coverage probability versus SINR threshold for $\kappa=1$. (a) MSP ordering. (b) ISINR ordering. (c) Comparison of MSP & ISINR ordering for ERPA scheme.
• Figure 5: Coverage probability versus SINR threshold for $\kappa=2$. (a) MSP ordering. (b) ISINR ordering. (c) Comparison of MSP & ISINR ordering under ERPA scheme.

Theorems & Definitions (14)

• Lemma 1
• proof
• Theorem 1
• proof
• Theorem 2
• proof
• Corollary 1
• proof
• Corollary 2
• proof