This letter investigates a fluid antenna (FA)-assisted integrated sensing and communication (ISAC) system, with joint antenna position optimization and waveform design. We consider enhancing the sum-rate maximization (SRM) and sensing performance with the aid of FAs. Although the introduction of FAs brings more degrees of freedom for performance optimization, its position optimization poses a non-convex programming problem and brings great computational challenges. This letter contributes to building an efficient design algorithm by the block successive upper bound minimization and majorization-minimization principles, with each step admitting closed-form update for the ISAC waveform design. In addition, the extrapolation technique is exploited further to speed up the empirical convergence of FA position design. Simulation results show that the proposed design can achieve state-of-the-art sum-rate performance with at least 60% computation cutoff compared to existing works with successive convex approximation (SCA) and particle swarm optimization (PSO) algorithms.

翻译：本文研究了一种流体天线（FA）辅助的集成传感与通信（ISAC）系统，涉及天线位置联合优化与波形设计。我们考虑借助FA来提升和速率最大化（SRM）与传感性能。尽管FA的引入为性能优化带来了更多自由度，但其位置优化构成了一个非凸规划问题，并带来了巨大的计算挑战。本文通过块连续上界最小化与主化-最小化原理，构建了一种高效的设计算法，其中ISAC波形设计的每一步都允许闭式更新。此外，进一步利用外推技术来加速FA位置设计的经验收敛速度。仿真结果表明，与采用连续凸近似（SCA）和粒子群优化（PSO）算法的现有工作相比，所提出的设计能够实现最先进的和速率性能，且计算量至少减少60%。