TY - JOUR
T1 - Intelligent Reflecting Surface-Assisted Localization
T2 - Performance Analysis and Algorithm Design
AU - Hua, Meng
AU - Wu, Qingqing
AU - Chen, Wen
AU - Fei, Zesong
AU - So, Hing Cheung
AU - Yuen, Chau
N1 - Publisher Copyright:
© 2012 IEEE.
PY - 2024/1/1
Y1 - 2024/1/1
N2 - The target sensing/localization performance is fundamentally limited by the line-of-sight link and severe signal attenuation over long distances. This letter considers a challenging scenario where the direct link between the base station (BS) and the target is blocked due to the surrounding blockages and leverages the intelligent reflecting surface (IRS) with some active sensors, termed as semi-passive IRS, for localization. To be specific, the active sensors receive echo signals reflected by the target and apply signal processing techniques to estimate the target location. We consider the joint time-of-arrival (ToA) and direction-of-arrival (DoA) estimation for localization and derive the corresponding Cramér-Rao bound (CRB), and then a simple ToA/DoA estimator without iteration is proposed. In particular, the relationships of the CRB for ToA/DoA with the number of frames for IRS beam adjustments, number of IRS reflecting elements, and number of sensors are theoretically analyzed and demystified. Simulation results show that the proposed semi-passive IRS architecture provides sub-meter level positioning accuracy even over a long localization range from the BS to the target and also demonstrate a significant localization accuracy improvement compared to the fully passive IRS architecture.
AB - The target sensing/localization performance is fundamentally limited by the line-of-sight link and severe signal attenuation over long distances. This letter considers a challenging scenario where the direct link between the base station (BS) and the target is blocked due to the surrounding blockages and leverages the intelligent reflecting surface (IRS) with some active sensors, termed as semi-passive IRS, for localization. To be specific, the active sensors receive echo signals reflected by the target and apply signal processing techniques to estimate the target location. We consider the joint time-of-arrival (ToA) and direction-of-arrival (DoA) estimation for localization and derive the corresponding Cramér-Rao bound (CRB), and then a simple ToA/DoA estimator without iteration is proposed. In particular, the relationships of the CRB for ToA/DoA with the number of frames for IRS beam adjustments, number of IRS reflecting elements, and number of sensors are theoretically analyzed and demystified. Simulation results show that the proposed semi-passive IRS architecture provides sub-meter level positioning accuracy even over a long localization range from the BS to the target and also demonstrate a significant localization accuracy improvement compared to the fully passive IRS architecture.
KW - Cramer-Rao bound (CRB)
KW - Intelligent reflecting surface (IRS)
KW - direction-of-arrival (DoA)
KW - target localization
KW - time-of-arrival (ToA)
UR - http://www.scopus.com/inward/record.url?scp=85174823133&partnerID=8YFLogxK
U2 - 10.1109/LWC.2023.3320728
DO - 10.1109/LWC.2023.3320728
M3 - Article
AN - SCOPUS:85174823133
SN - 2162-2337
VL - 13
SP - 84
EP - 88
JO - IEEE Wireless Communications Letters
JF - IEEE Wireless Communications Letters
IS - 1
ER -