可重构天线阵列ISAC系统的联合EM-BB波束成形设计

中文摘要 AI 辅助

本文研究了由图案和极化可重构像素天线阵列实现的集成感知与通信（ISAC）系统中的电磁（EM）域和基带（BB）域联合波束成形。开发了一种基于多端口网络的天线模型，利用从计算机仿真技术（CST）工作室套件仿真中提取的阻抗和开路辐射数据，将每个二进制开关配置映射到其辐射响应。基于该模型，为下行链路通信和统计目标感知构建了极化感知虚拟信道，从而形成一个混合整数非凸问题，该问题在用户信干噪比（SINR）和发射功率约束下最大化平均感知信噪比（SNR）。为了处理耦合的二进制和连续变量，我们提出了一种交替优化算法，其中EM域开关状态矩阵使用连续穷举布尔优化（SEBO）更新，BB域预编码器通过最小化最大化（MM）和二阶锥规划（SOCP）过程进行优化，感知合并器通过瑞利商更新获得。仿真结果表明，与固定贴片基准相比，所提出的设计实现了更高的感知SNR和更强的目标角度鲁棒性。

英文摘要

This paper investigates the joint electromagnetic (EM)-domain and baseband (BB)-domain beamforming for integrated sensing and communication (ISAC) systems enabled by pattern- and polarization-reconfigurable pixel-antenna arrays. A multiport-network-based antenna model is developed to map each binary switch configuration to its radiation response using the impedance and open-circuit radiation data extracted from Computer Simulation Technology (CST) Studio Suite simulations. Based on this model, polarization-aware virtual channels are constructed for downlink communication and statistical target sensing, leading to a mixed-integer nonconvex problem that maximizes the average sensing signal-to-noise ratio (SNR) subject to user signal-to-interference-plus-noise ratio (SINR) and transmit-power constraints. To handle the coupled binary and continuous variables, we propose an alternating optimization algorithm, in which the EM-domain switch-state matrices are updated using successive exhaustive Boolean optimization (SEBO), the BB-domain precoder is optimized via a minorization-maximization (MM) and second-order cone programming (SOCP) procedure, and the sensing combiner is obtained from a Rayleigh-quotient update. Simulation results show that the proposed design achieves higher sensing SNR and stronger target-angle robustness than the fixed-patch benchmark.

发表机构

• Dalian University of Technology（大连理工大学）
• Friedrich-Alexander-University Erlangen-Nuremberg (FAU)（弗里德里希·亚历山大·埃尔朗根-纽伦堡大学）

机构由 AI 辅助整理，请以论文原文为准。

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6 pages, 4 figures, conference