高动态ISAC中MIMO-OTFS和MIMO-OFDM的基本限制：基于天线阵列架构的视角
Fundamental Limits of MIMO ISAC: An Antenna Array Architecture Perspective
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- National Yang Ming Chiao Tung University（国立阳明交通大学）
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中文总结 AI 辅助
研究高动态ISAC中MIMO-OTFS和MIMO-OFDM基本限制，比较SA与ULA，利用随机主化框架分析遍历信道容量和CRB，发现SA在通信容量和感知精度上更优，指出空间几何是性能提升主要驱动因素。
中文摘要 AI 辅助
本文研究了高移动性环境中MIMO-OTFS和MIMO-OFDM集成感知与通信（ISAC）系统的基本限制，特别比较了稀疏阵列（SA）与传统均匀线性阵列（ULA）。高动态场景如V2X和卫星网络存在严重多普勒频移和快速时变信道，需要强大调制方案和高效阵列几何结构。提供了遍历信道容量和用于角度估计的克拉美-罗界（CRB）的统一理论分析。利用随机主化框架，研究表明SA通过创建更“均匀”的空间特征值分布始终优于ULA，这使多径环境去相关并增加通信容量。对于感知，证明角度CRB渐近地与阵列天线位置的二阶矩成反比，表明SA由于其增加的物理孔径实现了更高精度，提高幅度高达天线数量的平方。值得注意的是，分析表明在相对理想条件下，MIMO-OTFS和MIMO-OFDM在容量和角度估计方面具有相似的基本限制，表明空间几何而非波形是空间维度基本性能提升的主要驱动因素。
英文摘要
This paper investigates the fundamental limits of MIMO integrated sensing and communications (ISAC) systems, specifically comparing sparse arrays (SAs) against conventional uniform linear arrays (ULAs). A unified theoretical analysis of ergodic channel capacity and the Cramér$\unicode{x2013}$Rao bound (CRB) for angle estimation is developed while accounting for the array geometry. Utilizing the framework of stochastic majorization, the study reveals that SAs consistently outperform ULAs by creating a more $\unicode{x201C}$uniform$\unicode{x201D}$ spatial eigenvalue distribution, which decorrelates the multipath environment and increases communication capacity. For sensing, the paper proves that the angle CRB is inversely proportional to the array's second-order central moment of antenna positions asymptotically, demonstrating that SAs achieve superior accuracy$\unicode{x2014}$improving by up to the square of the number of antennas$\unicode{x2014}$due to their increased physical aperture. These analyses and conclusions are demonstrated to be also valid for MIMO ISAC systems employed with the modern waveforms OTFS and OFDM, suggesting that spatial geometry, rather than waveform, is the primary driver of fundamental performance gains in the spatial dimension.
