Cramer-Rao Lower Bounds for Positioning with Large Intelligent Surfaces

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceeding


We consider the potential for positioning with a system where antenna arrays are deployed as a large intelligent surface (LIS). We derive Fisher-informations and Cram\'{e}r-Rao lower bounds (CRLB) in closed-form for terminals along the central perpendicular line (CPL) of the LIS for all three Cartesian dimensions. For terminals at positions other than the CPL, closed-form expressions for the Fisher-informations and CRLBs seem out of reach, and we alternatively provide approximations (in closed-form) which are shown to be very accurate. We also show that under mild conditions, the CRLBs in general decrease quadratically in the surface-area for both the x and y dimensions. For the z-dimension (distance from the LIS), the CRLB decreases linearly in the surface-area when terminals are along the CPL. However, when terminals move away from the CPL, the CRLB is dramatically increased and then also decreases quadratically in the surface-area. We also extensively discuss the impact of different deployments (centralized and distributed) of the LIS.


Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Communication Systems
Original languageEnglish
Title of host publicationIEEE 86th Vehicular Technology Conference: VTC2017-Fall 24–27 Sep. 2017, Toronto, Canad
Publication statusPublished - 2018 Feb 12
Publication categoryResearch
Event2017 IEEE 86th Vehicular Technology Conference (VTC-Fall) - Hilton Toronto, Toronto, Canada
Duration: 2017 Sep 242017 Sep 27


Conference2017 IEEE 86th Vehicular Technology Conference (VTC-Fall)