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Rate-Matching Framework for RSMA-Enabled Multibeam LEO Satellite Communications

Jaehyup Seong, Juha Park, Juhwan Lee, Jungwoo Lee, Jung-Bin Kim, Wonjae Shin, H. Vincent Poor

TL;DR

This work tackles traffic-demand mismatches in overloaded multibeam LEO SATCOM under phase perturbations from channel estimation and feedback. It introduces a rate-matching framework based on RSMA and an SCA-based algorithm to minimize the squared error between target and offered rates while reducing transmit power, accounting for imperfect CSIT and CSIR. The framework leverages a common RSMA stream to mitigate inter-/intra-beam interference and uses SOC-constrained reformulations to enable efficient optimization. Numerical results based on 3GPP NTN settings show substantial improvements in traffic-demand satisfaction over SDMA, MMF-RSMA, and other baselines, highlighting the method’s practical potential for heterogeneous traffic in future LEO SATCOM systems.

Abstract

With the goal of ubiquitous global connectivity, multibeam low Earth orbit (LEO) satellite communication (SATCOM) has attracted significant attention in recent years. The traffic demands of users are heterogeneous within the broad coverage of SATCOM due to different geological conditions and user distributions. Motivated by this, this paper proposes a novel rate-matching (RM) framework based on rate-splitting multiple access (RSMA) that minimizes the difference between the traffic demands and offered rates while simultaneously minimizing transmit power for power-hungry satellite payloads. Moreover, channel phase perturbations arising from channel estimation and feedback errors are considered to capture realistic multibeam LEO SATCOM scenarios. To tackle the non-convexity of the RSMA-based RM problem under phase perturbations, we convert it into a tractable convex form via the successive convex approximation method and present an efficient algorithm to solve the RM problem. Through the extensive numerical analysis across various traffic demand distribution and channel state information accuracy at LEO satellites, we demonstrate that RSMA flexibly allocates the power between common and private streams according to different traffic patterns across beams, thereby efficiently satisfying users non-uniform traffic demands. In particular, the use of common messages plays a vital role in overcoming the limited spatial dimension available at LEO satellites, enabling it to manage inter- and intra-beam interference effectively in the presence of phase perturbation.

Rate-Matching Framework for RSMA-Enabled Multibeam LEO Satellite Communications

TL;DR

This work tackles traffic-demand mismatches in overloaded multibeam LEO SATCOM under phase perturbations from channel estimation and feedback. It introduces a rate-matching framework based on RSMA and an SCA-based algorithm to minimize the squared error between target and offered rates while reducing transmit power, accounting for imperfect CSIT and CSIR. The framework leverages a common RSMA stream to mitigate inter-/intra-beam interference and uses SOC-constrained reformulations to enable efficient optimization. Numerical results based on 3GPP NTN settings show substantial improvements in traffic-demand satisfaction over SDMA, MMF-RSMA, and other baselines, highlighting the method’s practical potential for heterogeneous traffic in future LEO SATCOM systems.

Abstract

With the goal of ubiquitous global connectivity, multibeam low Earth orbit (LEO) satellite communication (SATCOM) has attracted significant attention in recent years. The traffic demands of users are heterogeneous within the broad coverage of SATCOM due to different geological conditions and user distributions. Motivated by this, this paper proposes a novel rate-matching (RM) framework based on rate-splitting multiple access (RSMA) that minimizes the difference between the traffic demands and offered rates while simultaneously minimizing transmit power for power-hungry satellite payloads. Moreover, channel phase perturbations arising from channel estimation and feedback errors are considered to capture realistic multibeam LEO SATCOM scenarios. To tackle the non-convexity of the RSMA-based RM problem under phase perturbations, we convert it into a tractable convex form via the successive convex approximation method and present an efficient algorithm to solve the RM problem. Through the extensive numerical analysis across various traffic demand distribution and channel state information accuracy at LEO satellites, we demonstrate that RSMA flexibly allocates the power between common and private streams according to different traffic patterns across beams, thereby efficiently satisfying users non-uniform traffic demands. In particular, the use of common messages plays a vital role in overcoming the limited spatial dimension available at LEO satellites, enabling it to manage inter- and intra-beam interference effectively in the presence of phase perturbation.

Paper Structure

This paper contains 13 sections, 1 theorem, 43 equations, 16 figures, 1 table, 1 algorithm.

Table of Contents

  1. Introduction
  2. Related Works
  3. Motivations and Contributions
  4. Notations
  5. System Model and Problem Formulation
  6. Channel Model
  7. Imperfect Channel Model of the Satellite and Users
  8. Rate-Splitting Multiple Access Based Signal Model
  9. Problem Formulation
  10. Proposed RSMA-Based Rate-Matching Framework
  11. Performance Evaluation
  12. Conclusion
  13. Appendix: Proof of (\ref{['Derv_4']}) and (\ref{['Derv_5']})

Key Result

Lemma 1

$\hat{\mathbf{h}}_{k} \hat{\mathbf{h}}_{k}^{\sf{H}} \odot [e^{-\delta_{\sf{fb}}^{2}}\mathbf{1}_{N_{{\sf{t}}}} + (1-e^{-\delta_{\sf{fb}}^{2}})\mathbf{I}_{N_{{\sf{t}}}}]$ and $\hat{\mathbf{h}}_{k} \hat{\mathbf{h}}_{k}^{\sf{H}} \odot [(1-e^{-\frac{\delta_{\sf{ce}}^{2}}{2}})^{2}\mathbf{1}_{N_{{\sf{t}}}}

Figures (16)

  • Figure 1: System model of the proposed RSMA scheme, where the LEO satellite serves users requiring different traffics in a wide range of service coverage.
  • Figure 2: Beam pattern of four spot beams and location of users uniformly distributed within each beam.
  • Figure 3: Achievable rate comparison of each user under perfect CSIT and CSIR ($\delta_{\sf{fb}}=0^{\circ}, \delta_{\sf{ce}}=0^{\circ}$) when the traffic demand $\mathbf{r}_{\sf{target}}$ is $[2, 2, 3, 3.5, 4]^{\sf{T}}$.
  • Figure 4: Achievable rate comparison of each user under imperfect CSIT and CSIR ($\delta_{\sf{fb}}=5^{\circ}, \delta_{\sf{ce}}=2^{\circ}$) when the traffic demand $\mathbf{r}_{\sf{target}}$ is $[2, 2, 3, 3.5, 4]^{\sf{T}}$.
  • Figure 5: Portion of the common rate and private rate of each user for "RM-RSMA" under perfect CSIT and CSIR ($\delta_{\sf{fb}}=0^{\circ}, \delta_{\sf{ce}}=0^{\circ}$) when the traffic demand $\mathbf{r}_{\sf{target}}$ is $[2, 2, 3, 3.5, 4]^{\sf{T}}$.
  • ...and 11 more figures

Theorems & Definitions (6)

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