Rate-Splitting for Joint Unicast and Multicast Transmission in LEO Satellite Networks with Non-Uniform Traffic Demand

TL;DR

This work addresses rate matching for joint unicast and multicast transmission (NOUM) in LEO satellite networks with non-uniform traffic demands under imperfect CSIT. It introduces an RSMA-based rate-matching framework that uses LogSumExp to smooth the minimum common-rate term and expresses common-rate portions as a ratio to reformulate the problem into an unconstrained NEPv. A generalized power iteration (GPI) based algorithm, GPI-RS-NOUM, solves for the optimal joint precoding vector and common-rate portions, achieving superior traffic-demand satisfaction compared to several benchmarks across diverse scenarios. Numerical results demonstrate robust performance gains in both perfect and imperfect CSIT settings, highlighting the essential role of the common stream in managing inter-stream and inter-user interference while enabling multicast delivery. The approach offers a practical, scalable solution for stable, high-quality joint unicast and multicast service in LEO SATCOM, with potential extensions to multi-antenna receivers and machine learning–assisted precoding.

Abstract

Low Earth orbit (LEO) satellite communications (SATCOM) with ubiquitous global connectivity is deemed a pivotal catalyst in advancing wireless communication systems for 5G and beyond. LEO SATCOM excels in delivering versatile information services across expansive areas, facilitating both unicast and multicast transmissions via high-speed broadband capability. Nonetheless, given the broadband coverage of LEO SATCOM, traffic demand distribution within the service area is non-uniform, and the time/frequency/power resources available at LEO satellites remain significantly limited. Motivated by these challenges, we propose a rate-matching framework for non-orthogonal unicast and multicast (NOUM) transmission. Our approach aims to minimize the difference between offered rates and traffic demands for both unicast and multicast messages. By multiplexing unicast and multicast transmissions over the same radio resource, rate-splitting multiple access (RSMA) is employed to manage interference between unicast and multicast streams, as well as inter-user interference under imperfect channel state information at the LEO satellite. To address the formulated problems non-smoothness and non-convexity, the common rate is approximated using the LogSumExp technique. Thereafter, we represent the common rate portion as the ratio of the approximated function, converting the problem into an unconstrained form. A generalized power iteration (GPI)-based algorithm, coined GPI-RS-NOUM, is proposed upon this reformulation. Through comprehensive numerical analysis across diverse simulation setups, we demonstrate that the proposed framework outperforms various benchmarks for LEO SATCOM with uneven traffic demands.

Figures (9)

• Figure 1: System model of the proposed RSMA-based NOUM transmission.
• Figure 2: Achievable rate comparison for each message. The unicast and multicast traffic demands are set to be $\mathbf{r}_{\sf target, uc} = [0.5, 0.5, 1, 1, 1.5, 2, 2.5, 2.5]^{\sf{T}}$ bps/Hz and $R_{\sf target, mc} = 1$ bps/Hz.
• Figure 3: Rate portion comparison between GPI-RS-NOUM and LDM-RM-NOUM for each message under perfect CSIT. The unicast and multicast traffic demands are set to be $\mathbf{r}_{\sf target, uc} = [0.5, 0.5, 1, 1, 1.5, 2, 2.5, 2.5]^{\sf{T}}$ and $R_{\sf target, mc} = 1$ bps/Hz.
• Figure 4: Comparison of CDF per MAE between the traffic demands and offered rates. The unicast and multicast traffic demands are set as $\mathbf{r}_{\sf target, uc} = [0.5, 0.5, 1, 1, 1.5, 2, 2.5, 2.5]^{\sf{T}}$ bps/Hz and $R_{\sf target, mc} = 1$ bps/Hz.
• Figure 5: Comparison of AMAE per multicast traffic demand. The unicast traffic demands are set as $\mathbf{r}_{\sf target, uc} = [0.5, 0.5, 1, 1, 1.5, 2, 2.5, 2.5]^{\sf{T}}$ bps/Hz.

Theorems & Definitions (8)

• Remark 1
• Lemma 1
• proof
• Lemma 2
• proof
• Remark 2
• Remark 3
• Remark 4