AI 中文总结
研究下一代低地球轨道卫星星座通信瓶颈，提出基于超表面天线架构，通过联合优化调度与波束成形制定加权和速率最大化问题，给出基于交替优化的算法，仿真验证其对低地球轨道卫星星座通信的有效性。
AI 中文摘要
下一代低地球轨道（LEO）卫星星座在频谱效率和机载硬件复杂性上面临关键瓶颈。为克服这些限制，本文引入了一种由LEO卫星上的超表面天线（MA）实现的新颖架构。MA是超表面集成馈电天线，可直接在波域执行高精度波束成形，有效减轻多用户干扰。基于此天线架构，通过联合优化向地面用户（TU）的馈电天线调度和超表面的无源波束成形，制定加权和速率（WSR）最大化问题。为解决此混合整数非线性规划（MINLP）挑战，提出了一种基于交替优化（AO）的联合调度和波束成形算法。一方面，该算法结合了多项式时间最小成本最大流（MCMF）方法，用于馈电天线和TU的最优调度。另一方面，它采用了与半定松弛（SDR）技术集成的加权最小均方误差（WMMSE）方法，专为超表面波束成形设计。仿真结果证实了该算法对基于MA的LEO卫星星座通信的有效性。
英文摘要
Next-generation low Earth orbit (LEO) satellite constellations face critical bottlenecks in spectral efficiency and onboard hardware complexity. To overcome these limitations, this paper introduces a novel architecture enabled by metasurface antennas (MAs) at the LEO satellites. In particular, MAs are metasurface-integrated feed antennas that perform high-precision beamforming directly in the wave domain, thereby effectively mitigating multi-user interference. Based on such an antenna architecture, a weighted sum rate (WSR) maximization problem is formulated by jointly optimizing the scheduling of feed antennas to terrestrial users (TUs) and the passive beamforming of the metasurface for system performance enhancement. To address this mixed-integer nonlinear programming (MINLP) challenge, an alternating optimization (AO)-based joint scheduling and beamforming algorithm is proposed. On the one hand, the proposed algorithm incorporates a polynomial-time minimum-cost maximum-flow (MCMF) method, which is dedicated to the optimal scheduling of feed antennas and TUs. On the other hand, it adopts a weighted minimum mean square error (WMMSE) method integrated with semidefinite relaxation (SDR) technique, which is tailored for metasurface beamforming design. Simulation results confirm the effectiveness of the proposed algorithm for MA-enabled LEO satellite constellation communications.
