自定位中最优RIS布置在布置误差下的鲁棒性保证
Robustness Guarantees for Optimal RIS Placement in Self-Localization Under Placement Errors
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中文总结 AI 辅助
本文证明在适度的独立同分布高斯位置误差下，RIS布置误差仅缩放CRB，不改变A/D/E最优布置，仿真验证了鲁棒性。
中文摘要 AI 辅助
本文研究了可重构智能表面（RIS）布置误差对基于飞行时间（ToF）的自定位中最优RIS部署的影响。我们考虑一个场景，其中信源发射信号，接收RIS反射的回波，并根据相应的ToF测量估计自身位置。在适度的独立同分布（i.i.d.）高斯RIS位置误差和i.i.d.高斯ToF噪声条件下，我们证明布置不确定性表现为Cramér-Rao下界（CRB）中一个与几何无关的缩放因子。因此，我们证明了RIS位置误差的存在不会改变最优RIS布置。该结果针对A-、D-和E-最优性准则建立。仿真结果验证了分析，并表明即使在存在布置不确定性的情况下，优化的RIS部署仍保持其优势。
英文摘要
This paper studies the effect of Reconfigurable Intelligent Surface (RIS) placement errors on optimal RIS deployment for Time-of-Flight (ToF)-based self-localization. We consider a setup in which a source transmits a signal, receives the RIS-reflected echo, and estimates its own position from the corresponding ToF measurements. Under the conditions of moderate, i.i.d. Gaussian RIS position errors and i.i.d. Gaussian ToF noise, we demonstrate that the placement uncertainty manifests as a geometry-independent scaling factor in the Cramér-Rao Bound (CRB). Consequently, we prove that the optimal RIS placement remains unchanged by the presence of RIS position errors. This result is established for A-, D-, and E-optimality criteria. Simulation results verify the analysis and show that optimized RIS deployments retain their advantage even in the presence of placement uncertainty.
发表机构
- Sharif University of Technology（谢里夫理工大学）
- Isfahan University of Technology（伊斯法罕理工大学）
机构由 AI 辅助整理，请以论文原文为准。
