Joint Resource Allocation and Beamforming Design for STAR-BD-RIS-Assisted LEO Satellite Collaborative Edge Computing

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Abstract
Low earth orbit (LEO) satellite-assisted edge computing is a promising paradigm for providing seamless connectivity to remote areas and enabling reliable services in dense urban scenarios. By establishing virtual line-of-sight (LoS) links and coherently combining reflected signals, the reconfigurable intelligent surface (RIS) can significantly enhance the channel conditions of satellite-terrestrial communication links. This paper integrates the novel simultaneously transmitting and reflecting beyond-diagonal RIS (STAR-BD-RIS) technology into the LEO satellite collaborative edge computing (LSCEC) system, where each ground user equipment (GUE) can simultaneously offload task bits to multiple satellites via a hybrid non-orthogonal multiple access (NOMA) scheme with the aid of STAR-BD-RIS. To minimize the weighted sum energy consumption of GUEs and LEO satellites, the transmit power, CPU frequency, offloading strategy, bandwidth allocation, and STAR-BD-RIS beamforming are jointly optimized by an iterative algorithm based on the successive convex approximation (SCA) technique and the penalty dual decomposition (PDD) method. Simulation results illustrate that: 1) the STAR-BD-RIS scheme achieves lower energy consumption than traditional RIS (T-RIS), simultaneously transmitting and reflecting RIS (STAR-RIS) and beyond-diagonal RIS (BD-RIS) schemes in LSCEC systems; 2) the proposed hybrid NOMA demonstrates superior scalability and performance over both NOMA and orthogonal frequency division multiple access (OFDMA); 3) the proposed satellite collaboration scheme significantly reduces the energy consumption compared to the case without collaboration, while exhibiting diminishing energy-saving gains as the number of satellites increases.
Funding Information
  • Fujian Zhongmin Offshore Wind Power Company Ltd (PHWFDSSC-HT-2026003)
  • Beijing Natural Science Foundation (L232041)

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