Pinching antenna (PA) systems have recently emerged as a promising flexible-antenna technology, which can reconstruct the wireless propagation environment by dynamically adjusting the positions of pinching elements along dielectric waveguides, thereby providing new spatial degrees of freedom (DoFs) for enhancing wireless system performance. This paper investigates a multi-waveguide PA-based multi-cell communication system, focusing on the joint optimization of precoding matrices, waveguide power allocation, and antenna placement to maximize the weighted sum rate (WSR). In multi-cell scenarios, inter-cell interference typically leads to a highly coupled and nonconvex WSR maximization problem. To address this challenge, an efficient alternating optimization framework is adopted to optimize each variable in an iterative way. Specifically, fractional programming is first employed to reformulate the original problem by introducing auxiliary variables that decouple the signal and interference terms. Based on this reformulation, block coordinate descent is then applied to optimize the precoding matrices and power allocation, leading to closed-form or semi-closed-form updates. For the high-dimensional and nonconvex PA placement problem, particle swarm optimization (PSO) is utilized to perform an efficient search and improve scalability. Numerical results demonstrate that, under various system configurations, the proposed scheme significantly outperforms baseline methods, including average power allocation, fixed antenna placement, conventional multiple-input multiple-output (MIMO), and massive MIMO. These results highlight the strong potential of PA systems for large-scale multi-cell wireless communications.

翻译：捏合天线（PA）系统近年来作为一种有前景的柔性天线技术出现，它通过沿介质波导动态调整捏合元件的位置，能够重构无线传播环境，从而为提升无线系统性能提供新的空间自由度（DoFs）。本文研究了一种基于多波导PA的多小区通信系统，重点针对预编码矩阵、波导功率分配及天线布置的联合优化问题，以实现加权和速率（WSR）最大化。在多小区场景中，小区间干扰通常会导致一个高度耦合且非凸的WSR最大化问题。为应对这一挑战，本文采用了一种高效的交替优化框架，以迭代方式优化每个变量。具体而言，首先通过引入辅助变量解耦信号与干扰项，利用分式规划对原问题进行重构。基于该重构，再应用块坐标下降法优化预编码矩阵和功率分配，得到闭式或半闭式更新解。针对高维且非凸的PA布置问题，采用粒子群优化（PSO）进行高效搜索并提升可扩展性。数值结果表明，在不同系统配置下，所提方案显著优于基线方法，包括平均功率分配、固定天线布置、传统多输入多输出（MIMO）及大规模MIMO。这些结果凸显了PA系统在大规模多小区无线通信中的巨大潜力。