High-capacity satellite network is the cornerstone of future space-air-ground integrated networks. However, the satellite uplink transmissions still face critical challenges, including severe path loss, complex multi-user interference, and payload constraints. Recently, Reconfigurable Intelligent Surfaces (RIS) and Fluid Antenna Systems (FAS) have shown promise for satellite communications through their dynamic signal reconfiguration. This paper proposes a multi-RIS-assisted satellite Compact Ultra-Massive Antenna Array (CUMA) architecture for multi-user satellite uplink transmission. Specifically, we deploy multiple RISs on the terrestrial side to separate interfering Line-of-Sight (LoS) channels via optimized phase shifts, and adopt a CUMA receiver on the satellite to further mitigate interference through FAS port selection. To solve a sum-rate maximization problem, we alternately optimize FAS port selection using a Forward-Backward Greedy Selection (FBGS) algorithm and RIS phase shifts based on Fractional Programming (FP). To the best of our knowledge, this is the first work to jointly optimize multi-RIS and CUMA in a satellite uplink context, where strong LoS and extreme path loss fundamentally distinguish the design from terrestrial counterparts. Simulation results confirm the effectiveness of the proposed architecture across frequency bands. At 6 GHz, our scheme achieves 181% and 32% rate gains over fixed antennas and traditional CUMA schemes, respectively, while the gains also reach 138% and 27% at 26 GHz, illustrating superiority in both interference-limited and noise-limited regimes.
Kai Feng, Runke Fan, Tianheng Xu et al.· IEEE Open Journal of the Com...· 0 citations
Fluid Antennas (FAs)-assisted Unmanned Aerial Vehicle (UAV) networks leverage the FA position adaptivity and flexible beamforming to overcome the limitations of Fixed-Positioned Antennas (FPAs) in dynamic UAV channels and Multi-User (MU) interference. This letter investigates a dual FA-assisted UAV network for MU-Multiple-Input-Multiple-Output (MIMO) downlink communications, aiming to maximize the average achievable rate through the joint optimization of UAV trajectory, the transmit/receive FA positions, and beamforming. The formulated problem is highly coupled and non-convex. Accordingly, an efficient Alternating Optimization (AO)-based algorithm is developed for decomposed subproblems, yielding a suboptimal solution. Numerical results demonstrate significant performance gains of 120% and 110% over conventional FPA-based and existing FA-based baselines, respectively.
Runke Fan, Tianheng Xu, Pei Peng et al.· 0 citations
As the role of satellites in sixth generation mobile communications system becomes increasingly well defined, satellite-terrestrial communications face an urgent need to improve spectral efficiency while ensuring user fairness. In this paper, we propose a multiple transmissive reconfigurable intelligent surfaces (RISs)-aided satellite-terrestrial downlink transmission scheme with rate-splitting multiple access. Based on statistical channel state information, we formulate a max-min user ergodic rate problem by jointly optimizing the satellite precoding, the phase shifts of multiple RISs, and the common-rate allocation. To tackle the resulting non-convex problem, we derive approximate closed-form expressions of multi-user ergodic rates and equivalently reformulate the problem via fractional programming. We then design a block coordinate descent-based algorithm to solve the transformed problem. Simulation results verify that the designed transmission scheme achieves significant performance gains in improving minimum user ergodic rate.
Kai Feng, Tianheng Xu, F. Takawira et al.· 2026 6th International Confe...· 0 citations