标题： 可移动天线辅助的LEO ISAC系统的联合波束赋形与定位设计 显示英文标题

标题： Joint Beamforming and Position Design for Movable Antenna Assisted LEO ISAC Systems

摘要： 低地轨道（LEO）卫星辅助的集成感知与通信（ISAC）系统已被广泛研究，以实现无处不在的连接。 然而，LEO卫星的严重信号衰减和有限的发射功率会降低ISAC性能。 为解决这一问题，本文研究了移动天线（MA）辅助的LEO ISAC系统。 我们推导了通信信噪比加干扰比（SINR）和感知平方定位误差界限（SPEB），以评估ISAC性能。 然后，我们联合优化发射波束成形和MA位置，以在SINR约束、总发射功率约束和MA阵列的几个固有物理约束下最小化SPEB。 我们首先使用半定松弛（SDR）简化复杂问题。 然后，我们提出了一种新颖的交替优化（AO）算法，将原始问题解耦为两个子问题，从而使其凸化并求解。 仿真结果表明了所提算法的收敛性和有效性。 与基准相比，实现了更好的通信与感知性能之间的权衡，感知性能至少提高了25%。 显示英文摘要

摘要： Low earth orbit (LEO) satellite-assisted integrated sensing and communications (ISAC) systems have been extensively studied to achieve ubiquitous connectivity. However, the severe signal attenuation and limited transmit power at LEO satellites can degrade ISAC performance. To address this issue, this paper investigated movable antenna (MA)-assisted LEO ISAC systems. We derive the communication signal-to-interference-plus-noise ratio (SINR) and the sensing squared position error bound (SPEB) for evaluating the ISAC performance. Then, we jointly optimize the transmit beamforming and the MA positions to minimize the SPEB under the SINR constraints, total transmit power constraint, and several inherent physical constraints of the MA array. We first simplify the complex problem using the semidefinite relaxation (SDR). Then, we present a novel alternating optimization (AO)-based algorithm to decouple the original problem into two subproblems, consequently convexified and solved. Simulations demonstrate the convergence and effectiveness of the proposed algorithm. Better trade-off between communication and sensing performance, and at least 25% gain in sensing performance are achieved, compared to the benchmarks.