目标角度不确定性下的大规模MIMO ISAC：CRLB中断分析与鲁棒资源分配
Massive MIMO ISAC Under Target-Angle Uncertainty: CRLB Outage Analysis and Robust Resource Allocation
中文总结 AI 辅助
针对目标角度估计误差导致的大规模MIMO ISAC系统感知性能下降问题，本文推导了CRLB闭式表达式及中断概率，并提出联合优化导频与发射功率的鲁棒分配框架，显著降低中断概率并提升通信和速率。
中文摘要 AI 辅助
在集成感知与通信（ISAC）中，相同的频谱和硬件资源被共享用于两种功能。大多数ISAC设计假设完美的目标角度信息，忽略了角度估计误差，这些误差会导致导向矢量失配、降低感知精度，并可能使确定性感知保证失效。本文研究了在目标角度估计不完善情况下的单站大规模多输入多输出（MIMO）ISAC系统。我们推导了在角度不确定性存在时，目标方位角和仰角估计的克拉美-罗下界（CRLBs）的闭式表达式。我们刻画了在高斯、广义均匀和von Mises角度误差模型下CRLBs的累积分布函数和中断概率。我们的分析表明，在小误差区域，由于发射导向矢量失配，CRLBs随角度误差二次方增加。为确保可靠的感知，我们提出了一种鲁棒功率分配框架，该框架联合优化导频训练和通信/感知发射功率，以在满足CRLB中断约束的同时最大化通信和速率。所得非凸问题通过基于连续凸逼近的交替优化算法求解。数值结果验证了所开发的分析，并表明所提出的鲁棒设计相比传统非鲁棒方案，可将方位角和仰角CRLB中断概率降低高达60%。在严格的CRLB阈值下，它比非鲁棒设计获得高达45%更高的和速率。
英文摘要
In integrated sensing and communications (ISAC), the same spectral and hardware resources are shared for two functionalities. Most ISAC designs assume perfect target-angle information neglecting angle estimation errors, which introduce steering-vector mismatches, degrade sensing accuracy, and may invalidate deterministic sensing guarantees. This paper investigates monostatic massive multiple-input-multiple-output (MIMO) ISAC systems under imperfect target-angle estimates. We derive closed-form expressions for the Cramér-Rao lower bounds (CRLBs) of target azimuth and elevation estimates in the presence of angle uncertainty. We characterize the cumulative distribution functions and outage probabilities of the CRLBs under Gaussian, generalized uniform, and von Mises angle-error models. Our analysis reveals that, in the small-error regime, the CRLBs increase quadratically with the angle errors due to transmit steering-vector mismatch. To ensure reliable sensing, we propose a robust power allocation framework that jointly optimizes pilot training and communications/sensing transmission powers to maximize the communications sum rate while satisfying CRLB outage constraints. The resulting nonconvex problem is solved using an alternating-optimization algorithm based on successive convex approximation. Numerical results validate the developed analysis and show that the proposed robust design reduces azimuth and elevation CRLB outage probabilities by up to $60\%$ compared with conventional non-robust schemes. It attains up to $45\%$ higher sum rates than the non-robust design under strict CRLB thresholds.
